Slideshow of the presentation given at Eusiipco 2016
Due to its possible low-power implementation, Compressed Sensing (CS) is an attractive tool for physiological signal acquisition in emerging scenarios like Wireless Body Sensor Networks (WBSN) and telemonitoring applications. In this work we consider the continuous monitoring and analysis of the fetal ECG signal (fECG). We propose a modification of the low-complexity CS reconstruction SL0 algorithm, improving its robustness in the presence of noisy original signals and possibly ill-conditioned sensing/reconstruction procedures. We show that, while maintaining the same computational cost of the original algorithm, the proposed modification significantly improves the reconstruction quality, both for synthetic and real-world ECG signals. We also show that the proposed algorithm allows robust heart beat classification when sparse matrices, implementable with very low computational complexity, are used for compressed sensing of the ECG signal.
Gaussian Dictionary for Compressive Sensing of the ECG SignalRiccardo Bernardini
Slideshow of the presentation given at the IEEE Workshop on Biometric Measurements and Systems for Security and Medical applications (2014)
Compressive Sensing (CS) is a newly introduced signal processing technique that enables to recover sparse signals from fewer samples than the Shannon sampling theorem would typically require. It is based on the assumption that, for a sparse signal, a small collection of linear measurements contains enough information to allow its reconstruction. Combining the acquisition and compression stages, CS is a very promising technique to develop ultra low power wireless bio-signal monitoring systems. In this paper we present a Compressive Sensing framework for ECG signals based on a universal Gaussian over-complete dictionary that permits to successfully increase the reconstruction quality performance. The purpose of the proposed dictionary is to improve ECG signal sparsity in order to achieve a higher compression ratio. Numerical experiments demonstrate that our method achieves improved performance with respect to state-of-the-art CS schemes.
The Indus Valley Civilisation (IVC) was a Bronze Age civilisation (3300–1300 BCE; mature period 2600–1600 BCE) mainly in the northwestern regions of the South Asia, extending from what today is northeast Afghanistan to Pakistan and northwest India.
Along with ancient Egypt and Mesopotamia it was one of three early civilisations of the Old World, and of the three, the most widespread.
It flourished in the basins of the Indus River, which flows through the length of Pakistan, and along a system of perennial, mostly monsoon-fed, rivers that once coursed in the vicinity of the seasonal Ghaggar-Hakra river in northwest India and eastern Pakistan.
A novel high resolution doa estimation design algorithm of close sources sign...eSAT Journals
Abstract Underwater target finding in ocean environment has gain considerable interest in both military and civilian applications. In this paper the performance of directions finding techniques, subspace and the non-subspace methods are presented. In this paper, the Eigen analysis of high resolution and supreme resolution algorithms, comparisons and the performance, resolution analysis are done. The analysis is based on linear array elements and the calculation of the pseudo spectra function of the valuation algorithms. Traditional MUSIC algorithm decomposes the signal covariance matrix and then make the signals subspace obtained is orthogonal to the noise subspace, which decreases the effect of the noise. But when the signals intervals are very small, traditional improved MUSIC algorithm has been unable to distinguish the signals as the SNR decreases. A new improved algorithm is introduced using Singular value decomposition of the covariance matrix. An antenna of ULA configuration is taken for both the algorithms. Simulation results show that projected method gives better performance than MUSIC algorithm. In this newly Modified MUSIC algorithm, conditions required for under water environment are taken into account such as water density, permittivity of water, pressure, Signal to Noise Ratio, speed of sound wave in water. Keywords: Underwater Communication, Number of Snapshots, Antenna Noise, Uniform Linear Array (ULA) and Distance Between Array Elements.
Gaussian Dictionary for Compressive Sensing of the ECG SignalRiccardo Bernardini
Slideshow of the presentation given at the IEEE Workshop on Biometric Measurements and Systems for Security and Medical applications (2014)
Compressive Sensing (CS) is a newly introduced signal processing technique that enables to recover sparse signals from fewer samples than the Shannon sampling theorem would typically require. It is based on the assumption that, for a sparse signal, a small collection of linear measurements contains enough information to allow its reconstruction. Combining the acquisition and compression stages, CS is a very promising technique to develop ultra low power wireless bio-signal monitoring systems. In this paper we present a Compressive Sensing framework for ECG signals based on a universal Gaussian over-complete dictionary that permits to successfully increase the reconstruction quality performance. The purpose of the proposed dictionary is to improve ECG signal sparsity in order to achieve a higher compression ratio. Numerical experiments demonstrate that our method achieves improved performance with respect to state-of-the-art CS schemes.
The Indus Valley Civilisation (IVC) was a Bronze Age civilisation (3300–1300 BCE; mature period 2600–1600 BCE) mainly in the northwestern regions of the South Asia, extending from what today is northeast Afghanistan to Pakistan and northwest India.
Along with ancient Egypt and Mesopotamia it was one of three early civilisations of the Old World, and of the three, the most widespread.
It flourished in the basins of the Indus River, which flows through the length of Pakistan, and along a system of perennial, mostly monsoon-fed, rivers that once coursed in the vicinity of the seasonal Ghaggar-Hakra river in northwest India and eastern Pakistan.
A novel high resolution doa estimation design algorithm of close sources sign...eSAT Journals
Abstract Underwater target finding in ocean environment has gain considerable interest in both military and civilian applications. In this paper the performance of directions finding techniques, subspace and the non-subspace methods are presented. In this paper, the Eigen analysis of high resolution and supreme resolution algorithms, comparisons and the performance, resolution analysis are done. The analysis is based on linear array elements and the calculation of the pseudo spectra function of the valuation algorithms. Traditional MUSIC algorithm decomposes the signal covariance matrix and then make the signals subspace obtained is orthogonal to the noise subspace, which decreases the effect of the noise. But when the signals intervals are very small, traditional improved MUSIC algorithm has been unable to distinguish the signals as the SNR decreases. A new improved algorithm is introduced using Singular value decomposition of the covariance matrix. An antenna of ULA configuration is taken for both the algorithms. Simulation results show that projected method gives better performance than MUSIC algorithm. In this newly Modified MUSIC algorithm, conditions required for under water environment are taken into account such as water density, permittivity of water, pressure, Signal to Noise Ratio, speed of sound wave in water. Keywords: Underwater Communication, Number of Snapshots, Antenna Noise, Uniform Linear Array (ULA) and Distance Between Array Elements.
Assessment of likely consequences of a potential accident is a major concern for loss prevention and
safety promotion in process industry. Loss of confinement on a storage tank, vessel or piping on industrial
sites could imply atmospheric dispersion of toxic or flammable gases. Gas dispersion forecasting is a
difficult task since turbulence modeling at large scale involves expensive calculations. Therefore simpler
models are used but remain inaccurate especially when turbulence is heterogeneous. The present work
aims to study if Artificial Neural Networks coupled with Cellular Automata could be relevant to overcome
these gaps. Two methods are reviewed and compared. An example database was designed from RANS k-
ε CFD model. Both methods were then applied. Their efficiencies are compared and discussed in terms of
quality, real-time applicability and real-life plausibility.
Projected Barzilai-Borwein Methods Applied to Distributed Compressive Spectru...Polytechnique Montreal
Cognitive radio allows unlicensed (cognitive) users to use licensed frequency bands by exploiting spectrum sensing techniques to detect whether or not the licensed (primary) users are present. In this paper, we present a compressed sensing applied to spectrum-occupancy detection in wide-band applications. The collected analog signals from each cognitive radio (CR) receiver at a fusion center are transformed to discrete-time signals by using analog-to-information converter (AIC) and then employed to calculate the autocorrelation. For signal reconstruction, we exploit a novel approach to solve the optimization problem consisting of minimizing both a quadratic (l2) error term and an l1-regularization term. In specific, we propose the Basic gradient projection (GP) and projected Barzilai-Borwein (PBB) algorithm to offer a better performance in terms of the mean squared error of the power spectrum density estimate and the detection probability of licensed signal occupancy.
Attention gated encoder-decoder for ultrasonic signal denoisingIAESIJAI
Ultrasound imaging is one of the most widely used non-destructive testing methods. The transducer emits pulses that travel through the imaged samples and are reflected by echo-forming impedance. The resulting ultrasonic signals usually contain noise. Most of the traditional noise reduction algorithms require high skills and prior knowledge of noise distribution, which has a crucial impact on their performances. As a result, these methods generally yield a loss of information, significantly influencing the final data and deeply limiting both sensitivity and resolution of imaging devices in medical and industrial applications. In the present study, a denoising method based on an attention-gated convolutional autoencoder is proposed to fill this gap. To evaluate its performance, the suggested protocol is compared to widely used methods such as butterworth filtering (BF), discrete wavelet transforms (DWT), principal component analysis (PCA), and convolutional autoencoder (CAE) methods. Results proved that better denoising can be achieved especially when the original signal-to-noise ratio (SNR) is very low and the sound waves’ traces are distorted by noise. Moreover, the initial SNR was improved by up to 30 dB and the resulting Pearson correlation coefficient was maintained over 99% even for ultrasonic signals with poor initial SNR.
Performance analysis of compressive sensing recovery algorithms for image pr...IJECEIAES
The modern digital world comprises of transmitting media files like image, audio, and video which leads to usage of large memory storage, high data transmission rate, and a lot of sensory devices. Compressive sensing (CS) is a sampling theory that compresses the signal at the time of acquiring it. Compressive sensing samples the signal efficiently below the Nyquist rate to minimize storage and recoveries back the signal significantly minimizing the data rate and few sensors. The proposed paper proceeds with three phases. The first phase describes various measurement matrices like Gaussian matrix, circulant matrix, and special random matrices which are the basic foundation of compressive sensing technique that finds its application in various fields like wireless sensors networks (WSN), internet of things (IoT), video processing, biomedical applications, and many. Finally, the paper analyses the performance of the various reconstruction algorithms of compressive sensing like basis pursuit (BP), compressive sampling matching pursuit (CoSaMP), iteratively reweighted least square (IRLS), iterative hard thresholding (IHT), block processing-based basis pursuit (BP-BP) based on mean square error (MSE), and peak signal to noise ratio (PSNR) and then concludes with future works.
Non-Contact Health Monitoring System Using Image and Signal ProcessingAtul Kumar Sharma
Presently digital medical devices promise to transform the future of medicine because of their ability to produce exquisitely detailed individual physiological data. As ordinary people start to have access and control over their own physiological data so that they can play a more active role in the management of their health. Currently many techniques are available for counting our heartbeat but it all needs bundles of sensors and wires. For heartbeat measurement using Electrocardiograph(ECG) method, we have to attach a bundle of leads in our chest and have to use adhesive gel. It is very difficult to patients and it can cause irritation to the skin. Another type is pulse oximeters and sensors, in this method sensors are attached to the finger tips or earlobes. This is also difficult for user.
In case of "Non-contact health monitoring system using image and signal processing" which gives contact free measurement about our physiological information using basic image processing devices. Users have the experience of real time health monitoring by just looking into "medical mirror". It recognizes our heartbeat without any external or internal sensor and displays it in real time. This invention helps people to access their own physiological data.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Compressive Sensing in Speech from LPC using Gradient Projection for Sparse R...IJERA Editor
This paper presents compressive sensing technique used for speech reconstruction using linear predictive coding because the
speech is more sparse in LPC. DCT of a speech is taken and the DCT points of sparse speech are thrown away arbitrarily.
This is achieved by making some point in DCT domain to be zero by multiplying with mask functions. From the incomplete
points in DCT domain, the original speech is reconstructed using compressive sensing and the tool used is Gradient
Projection for Sparse Reconstruction. The performance of the result is compared with direct IDCT subjectively. The
experiment is done and it is observed that the performance is better for compressive sensing than the DCT.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal,
Performance Analysis of Fading Channels on Cooperative Mode Spectrum Sensing ...ijtsrd
Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. The sensing of radio spectrum is an essential problem in cognitive radio CR networks, where secondary users SUs need to detect the presence of primary users PUs before they use the spectrum allocated to PUs. The detection of primary user status and the spectrum sensing are the major issues in cognitive radio systems. We employ one of the simplest and most efficient Spectrum Sensing technique, the cooperative spectrum sensing with three different digital modulation techniques BPSK, QPSK, 16 QAM. In this paper, we analyze the performance of the cooperative spectrum sensing technique with BPSK, QPSK, 16 QAM modulation techniques over Rayleigh fading Channel. Further, we analyze the performance and BER Bit Error Rate of cooperative spectrum sensing under Rayleigh fading and AWGN channels. The investigation and analysis on cooperative spectrum sensing with above digital modulation techniques can be utilized for future reference of spectrum sensing in the CR networks over AWGN and Rayleigh fading channels. Sangram Singh | Rashmi Raj "Performance Analysis of Fading Channels on Cooperative Mode Spectrum Sensing Technique for Cognitive Radio" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30338.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/30338/performance-analysis-of-fading-channels-on-cooperative-mode-spectrum-sensing-technique-for-cognitive-radio/sangram-singh
Diabetic retinopathy is one of the leading complication of diabetes and also one of the leading preventable blindness. Early diagnosis and treatment may prevent such condition or in other words, annoyance of the disease may be overcome. The fundus images produced by automated fundus camera are often noisy making it difficult for doctors to precisely detect the abnormalities in fundus images. In the present paper, we propose to use vessel extraction of Retinal image enhancement and implemented in Raspberry Pi board using opencv library for faster execution and cost effective processing unit which helps during mass screening of diabetic retinopathy. The effectiveness of the proposed techniques is evaluated using different metrics and Micro-aneurysms. Finally, a considerable improvement in the enhancement of the Diabetic Retinopathy images is achieved.
Novel method to find the parameter for noise removal from multi channel ecg w...eSAT Journals
Abstract In general, electrocardiogram (ECG) waveforms are affected by noise and artifacts and it is essential to remove the noise in order to support any decision making for specialist. It is very difficult to remove the noise from 12 channel ECG waveforms using standard noise removal methodologies. Removal of the noise from ECG waveforms is majorly classified into two types in signal processing namely Digital filters and Analog filters. Digital filters are more accurate than analog filters because analog filters introduce nonlinear phase shift. Most advanced research digital filters are FIR and IIR.FIR filters are stable as they have non-recursive structure. They give the exact linear phase and efficiently realizable in hardware. The filter response is finite duration. Thus noise removal using FIR digital filter is better option in comparison with IIR digital filter. But it is very difficult to find the cut-off frequency parameter for dynamic multi-channel ECG waveforms using existing traditional methods. So, in this research, newly introduced Multi-Swarm Optimization (MSO) methodology for automatically identifying the cut-off frequency parameter of multichannel ECG waveforms for low-pass filtering is inspecting. Generally, the spectrums of the ECG waveforms are extracted from four classes: normal sinus rhythm, atria fibrillation, arrhythmia and supraventricular. Baseline wander is removed using the Moving Median Filter. A dataset of the extracted features of the ECG spectrums is used to train the MSO. The performance of the MSO with various parameters is investigated. Finally, the MSO-identified cut-off frequency parameter, it’s applied to a Finite Impulse Response (FIR) filter. The resulting signal is evaluated against the original clean and conventional filtered ECG signal. Keywords: 12 Channel ECG Waveforms, Multi Swarm Optimization Neural Network, Low-pass filtering, Finite Impulse Response (FIR).
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Slide show of a talk given at the Ada DevRoom at FOSDEM 2020 about eugen, a software that helps in writing project description (WP cards, deliverable, milestones, GANTT, ...) while guaranteeing coherence in the description.
Project Gitlab page: https://gitlab.com/mockturtle/eugen
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Assessment of likely consequences of a potential accident is a major concern for loss prevention and
safety promotion in process industry. Loss of confinement on a storage tank, vessel or piping on industrial
sites could imply atmospheric dispersion of toxic or flammable gases. Gas dispersion forecasting is a
difficult task since turbulence modeling at large scale involves expensive calculations. Therefore simpler
models are used but remain inaccurate especially when turbulence is heterogeneous. The present work
aims to study if Artificial Neural Networks coupled with Cellular Automata could be relevant to overcome
these gaps. Two methods are reviewed and compared. An example database was designed from RANS k-
ε CFD model. Both methods were then applied. Their efficiencies are compared and discussed in terms of
quality, real-time applicability and real-life plausibility.
Projected Barzilai-Borwein Methods Applied to Distributed Compressive Spectru...Polytechnique Montreal
Cognitive radio allows unlicensed (cognitive) users to use licensed frequency bands by exploiting spectrum sensing techniques to detect whether or not the licensed (primary) users are present. In this paper, we present a compressed sensing applied to spectrum-occupancy detection in wide-band applications. The collected analog signals from each cognitive radio (CR) receiver at a fusion center are transformed to discrete-time signals by using analog-to-information converter (AIC) and then employed to calculate the autocorrelation. For signal reconstruction, we exploit a novel approach to solve the optimization problem consisting of minimizing both a quadratic (l2) error term and an l1-regularization term. In specific, we propose the Basic gradient projection (GP) and projected Barzilai-Borwein (PBB) algorithm to offer a better performance in terms of the mean squared error of the power spectrum density estimate and the detection probability of licensed signal occupancy.
Attention gated encoder-decoder for ultrasonic signal denoisingIAESIJAI
Ultrasound imaging is one of the most widely used non-destructive testing methods. The transducer emits pulses that travel through the imaged samples and are reflected by echo-forming impedance. The resulting ultrasonic signals usually contain noise. Most of the traditional noise reduction algorithms require high skills and prior knowledge of noise distribution, which has a crucial impact on their performances. As a result, these methods generally yield a loss of information, significantly influencing the final data and deeply limiting both sensitivity and resolution of imaging devices in medical and industrial applications. In the present study, a denoising method based on an attention-gated convolutional autoencoder is proposed to fill this gap. To evaluate its performance, the suggested protocol is compared to widely used methods such as butterworth filtering (BF), discrete wavelet transforms (DWT), principal component analysis (PCA), and convolutional autoencoder (CAE) methods. Results proved that better denoising can be achieved especially when the original signal-to-noise ratio (SNR) is very low and the sound waves’ traces are distorted by noise. Moreover, the initial SNR was improved by up to 30 dB and the resulting Pearson correlation coefficient was maintained over 99% even for ultrasonic signals with poor initial SNR.
Performance analysis of compressive sensing recovery algorithms for image pr...IJECEIAES
The modern digital world comprises of transmitting media files like image, audio, and video which leads to usage of large memory storage, high data transmission rate, and a lot of sensory devices. Compressive sensing (CS) is a sampling theory that compresses the signal at the time of acquiring it. Compressive sensing samples the signal efficiently below the Nyquist rate to minimize storage and recoveries back the signal significantly minimizing the data rate and few sensors. The proposed paper proceeds with three phases. The first phase describes various measurement matrices like Gaussian matrix, circulant matrix, and special random matrices which are the basic foundation of compressive sensing technique that finds its application in various fields like wireless sensors networks (WSN), internet of things (IoT), video processing, biomedical applications, and many. Finally, the paper analyses the performance of the various reconstruction algorithms of compressive sensing like basis pursuit (BP), compressive sampling matching pursuit (CoSaMP), iteratively reweighted least square (IRLS), iterative hard thresholding (IHT), block processing-based basis pursuit (BP-BP) based on mean square error (MSE), and peak signal to noise ratio (PSNR) and then concludes with future works.
Non-Contact Health Monitoring System Using Image and Signal ProcessingAtul Kumar Sharma
Presently digital medical devices promise to transform the future of medicine because of their ability to produce exquisitely detailed individual physiological data. As ordinary people start to have access and control over their own physiological data so that they can play a more active role in the management of their health. Currently many techniques are available for counting our heartbeat but it all needs bundles of sensors and wires. For heartbeat measurement using Electrocardiograph(ECG) method, we have to attach a bundle of leads in our chest and have to use adhesive gel. It is very difficult to patients and it can cause irritation to the skin. Another type is pulse oximeters and sensors, in this method sensors are attached to the finger tips or earlobes. This is also difficult for user.
In case of "Non-contact health monitoring system using image and signal processing" which gives contact free measurement about our physiological information using basic image processing devices. Users have the experience of real time health monitoring by just looking into "medical mirror". It recognizes our heartbeat without any external or internal sensor and displays it in real time. This invention helps people to access their own physiological data.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Compressive Sensing in Speech from LPC using Gradient Projection for Sparse R...IJERA Editor
This paper presents compressive sensing technique used for speech reconstruction using linear predictive coding because the
speech is more sparse in LPC. DCT of a speech is taken and the DCT points of sparse speech are thrown away arbitrarily.
This is achieved by making some point in DCT domain to be zero by multiplying with mask functions. From the incomplete
points in DCT domain, the original speech is reconstructed using compressive sensing and the tool used is Gradient
Projection for Sparse Reconstruction. The performance of the result is compared with direct IDCT subjectively. The
experiment is done and it is observed that the performance is better for compressive sensing than the DCT.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal,
Performance Analysis of Fading Channels on Cooperative Mode Spectrum Sensing ...ijtsrd
Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. The sensing of radio spectrum is an essential problem in cognitive radio CR networks, where secondary users SUs need to detect the presence of primary users PUs before they use the spectrum allocated to PUs. The detection of primary user status and the spectrum sensing are the major issues in cognitive radio systems. We employ one of the simplest and most efficient Spectrum Sensing technique, the cooperative spectrum sensing with three different digital modulation techniques BPSK, QPSK, 16 QAM. In this paper, we analyze the performance of the cooperative spectrum sensing technique with BPSK, QPSK, 16 QAM modulation techniques over Rayleigh fading Channel. Further, we analyze the performance and BER Bit Error Rate of cooperative spectrum sensing under Rayleigh fading and AWGN channels. The investigation and analysis on cooperative spectrum sensing with above digital modulation techniques can be utilized for future reference of spectrum sensing in the CR networks over AWGN and Rayleigh fading channels. Sangram Singh | Rashmi Raj "Performance Analysis of Fading Channels on Cooperative Mode Spectrum Sensing Technique for Cognitive Radio" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30338.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/30338/performance-analysis-of-fading-channels-on-cooperative-mode-spectrum-sensing-technique-for-cognitive-radio/sangram-singh
Diabetic retinopathy is one of the leading complication of diabetes and also one of the leading preventable blindness. Early diagnosis and treatment may prevent such condition or in other words, annoyance of the disease may be overcome. The fundus images produced by automated fundus camera are often noisy making it difficult for doctors to precisely detect the abnormalities in fundus images. In the present paper, we propose to use vessel extraction of Retinal image enhancement and implemented in Raspberry Pi board using opencv library for faster execution and cost effective processing unit which helps during mass screening of diabetic retinopathy. The effectiveness of the proposed techniques is evaluated using different metrics and Micro-aneurysms. Finally, a considerable improvement in the enhancement of the Diabetic Retinopathy images is achieved.
Novel method to find the parameter for noise removal from multi channel ecg w...eSAT Journals
Abstract In general, electrocardiogram (ECG) waveforms are affected by noise and artifacts and it is essential to remove the noise in order to support any decision making for specialist. It is very difficult to remove the noise from 12 channel ECG waveforms using standard noise removal methodologies. Removal of the noise from ECG waveforms is majorly classified into two types in signal processing namely Digital filters and Analog filters. Digital filters are more accurate than analog filters because analog filters introduce nonlinear phase shift. Most advanced research digital filters are FIR and IIR.FIR filters are stable as they have non-recursive structure. They give the exact linear phase and efficiently realizable in hardware. The filter response is finite duration. Thus noise removal using FIR digital filter is better option in comparison with IIR digital filter. But it is very difficult to find the cut-off frequency parameter for dynamic multi-channel ECG waveforms using existing traditional methods. So, in this research, newly introduced Multi-Swarm Optimization (MSO) methodology for automatically identifying the cut-off frequency parameter of multichannel ECG waveforms for low-pass filtering is inspecting. Generally, the spectrums of the ECG waveforms are extracted from four classes: normal sinus rhythm, atria fibrillation, arrhythmia and supraventricular. Baseline wander is removed using the Moving Median Filter. A dataset of the extracted features of the ECG spectrums is used to train the MSO. The performance of the MSO with various parameters is investigated. Finally, the MSO-identified cut-off frequency parameter, it’s applied to a Finite Impulse Response (FIR) filter. The resulting signal is evaluated against the original clean and conventional filtered ECG signal. Keywords: 12 Channel ECG Waveforms, Multi Swarm Optimization Neural Network, Low-pass filtering, Finite Impulse Response (FIR).
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Similar to ROBUST RECONSTRUCTION FOR CS-BASED FETAL BEATS DETECTION (20)
Slide show of a talk given at the Ada DevRoom at FOSDEM 2020 about eugen, a software that helps in writing project description (WP cards, deliverable, milestones, GANTT, ...) while guaranteeing coherence in the description.
Project Gitlab page: https://gitlab.com/mockturtle/eugen
An overview of PPETP: a peer-to-peer protocol for live streaming of multimedia materials. Content-agnostic, it can be used transparently with any type of data. It appears to the programmer just as a multicast protocol.
Terra Bruciata: an open source initiative for software correctnessRiccardo Bernardini
Terra Bruciata is an initiative aiming to creating an open source community placing very strong emphasis on software correctness. Our wild dream is to make the third digit of version number useless because patches for bug correction should not be necessary anymore.
This is a slide show (with a peculiar graphical format :-) ) describing the main idea of this initiative.
Physically Unclonable Constants (PUC) are circuits used to embed unique secret bit-words in chips. We propose a simple PUC, employing two Schottkydiodes in reverse. The difference of the reverse currents of the two diodes is used to charge a capacitance. The charge stops when the two currents become equal. It is shown that this scheme has a single equilibrium point that depends discontinuously from the difference of the two saturation currents. The proposed scheme is studied both theoretically and by means of simulations (0.18 μm technology). It is shown that the proposed PUC is unbiased (inter distance %), very stable (intra distance from 2.8% to 1.5%) and temperature insensitive (only 0.3% of the cells changes output over a military temperature range). Energy required is predicted to be as small as 0.6 pJ/bit.
The problem of generating a sequence of true random bits (suitable for cryptographic applications) from random discrete or analog sources is considered. A generalized
version, including Vector Quantization, of the classical approach by Elias for the generation of truly random bits is
introduced, and its performance is analyzed, both in the finite case and asymptotically. The theory allows us to provide an alternative proof of the optimality of the original
Elias’ scheme. We also consider the problem of deriving
random bits from measurements of a Poisson process and
from vectors of iid Gaussian variables. The comparison with
the scheme of Elias, applied to geometric-like non binary
vectors, originally based on the iso-probability property of permutations of iid variables, confirms the potential of the generalized scheme proposed in our work.
The recent availability of reliable schemes for physically unclonable constants (PUC) opens interesting possibilities in the field of security. In this paper, we explore the possibility of using PUCs to embed in a chip random permutations to be used, for example, as building blocks in cryptographic constructions such as sponge functions, substitution–permutation networks, and so on. We show that the most difficult part is the generation of random integers using as the only randomness source the bit-string produced by the PUC. In order to solve the integer generation problem, we propose a partial rejection method that allows the designer to trade-off between entropy and efficiency. The results show that the proposed schemes can be implemented with reasonable complexity.
Full paper: "Making random permutations from physically unclonable constants" Bernardini, R. & Rinaldo, R. Int. J. Inf. Secur. (2016). doi:10.1007/s10207-016-0324-2
http://link.springer.com/article/10.1007/s10207-016-0324-2
Sparse Representation for Fetal QRS Detection in Abdominal ECG RecordingsRiccardo Bernardini
Slideshow of the presentation given at EHB 2015
In this work, we consider the problem of detection of fetal heart beats from abdominal, non-invasive mixture recordings. We propose a new method for the separation of maternal and fetal beats based on the sparse decomposition in an over-complete dictionary of Gaussian-like functions. To increase the detection capability, we also use Independent Component Analysis (ICA) after maternal template subtraction. We show that the proposed detection method can be applied on the original mixture with a sensitivity close to 95%. Moreover, our method may be used also for single channel abdominal ECG signals, and also used in real-time applications.
Slide show of the presentation given at Austrochip 2014 about a simple and very reliable PUF.
Physically unclonable constants (PUC) are circuits used to embed unique secret bit-words in chips. We propose a simple PUC, with a complexity comparable with an SRAM cell. The proposed scheme is studied both theoretically and by means of simulations and it is shown that the proposed PUC is both unbiased and very stable. In particular, its intra-distance is predicted to be from 10 to 100 times smaller than competitor schemes. Simulations allow to conclude that the advantages of the proposed scheme are relevant enough to make it competitive even if the actual performance of a real implementation, not considered in this paper, will turn out to be an order of magnitude worse than predicted.
See also
https://doi.org/10.1109/TIFS.2016.2599008
http://ieeexplore.ieee.org/document/7539631/
Slide show of the presentation given at Austrochip 2014.
Abstract:
Physically unclonable constants (PUC) are circuits used to embed unique secret bit-words in chips. We propose a simple PUC, with a complexity comparable with an SRAM cell. The proposed scheme is studied both theoretically and by means of simulations and it is shown that the proposed PUC is both unbiased and very stable. In particular, its intra-distance is predicted to be from 10 to 100 times smaller than competitor schemes. Simulations allow to conclude that the advantages of the proposed scheme are relevant enough to make it competitive even if the actual performance of a real implementation, not considered in this paper, will turn out to be an order of magnitude worse than predicted.
See also
http://ieeexplore.ieee.org/document/7539631/
https://doi.org/10.1109/TIFS.2016.2599008
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
An Approach to Detecting Writing Styles Based on Clustering Techniquesambekarshweta25
An Approach to Detecting Writing Styles Based on Clustering Techniques
Authors:
-Devkinandan Jagtap
-Shweta Ambekar
-Harshit Singh
-Nakul Sharma (Assistant Professor)
Institution:
VIIT Pune, India
Abstract:
This paper proposes a system to differentiate between human-generated and AI-generated texts using stylometric analysis. The system analyzes text files and classifies writing styles by employing various clustering algorithms, such as k-means, k-means++, hierarchical, and DBSCAN. The effectiveness of these algorithms is measured using silhouette scores. The system successfully identifies distinct writing styles within documents, demonstrating its potential for plagiarism detection.
Introduction:
Stylometry, the study of linguistic and structural features in texts, is used for tasks like plagiarism detection, genre separation, and author verification. This paper leverages stylometric analysis to identify different writing styles and improve plagiarism detection methods.
Methodology:
The system includes data collection, preprocessing, feature extraction, dimensional reduction, machine learning models for clustering, and performance comparison using silhouette scores. Feature extraction focuses on lexical features, vocabulary richness, and readability scores. The study uses a small dataset of texts from various authors and employs algorithms like k-means, k-means++, hierarchical clustering, and DBSCAN for clustering.
Results:
Experiments show that the system effectively identifies writing styles, with silhouette scores indicating reasonable to strong clustering when k=2. As the number of clusters increases, the silhouette scores decrease, indicating a drop in accuracy. K-means and k-means++ perform similarly, while hierarchical clustering is less optimized.
Conclusion and Future Work:
The system works well for distinguishing writing styles with two clusters but becomes less accurate as the number of clusters increases. Future research could focus on adding more parameters and optimizing the methodology to improve accuracy with higher cluster values. This system can enhance existing plagiarism detection tools, especially in academic settings.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Water billing management system project report.pdfKamal Acharya
Our project entitled “Water Billing Management System” aims is to generate Water bill with all the charges and penalty. Manual system that is employed is extremely laborious and quite inadequate. It only makes the process more difficult and hard.
The aim of our project is to develop a system that is meant to partially computerize the work performed in the Water Board like generating monthly Water bill, record of consuming unit of water, store record of the customer and previous unpaid record.
We used HTML/PHP as front end and MYSQL as back end for developing our project. HTML is primarily a visual design environment. We can create a android application by designing the form and that make up the user interface. Adding android application code to the form and the objects such as buttons and text boxes on them and adding any required support code in additional modular.
MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software. It is a stable ,reliable and the powerful solution with the advanced features and advantages which are as follows: Data Security.MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Planning Of Procurement o different goods and services
ROBUST RECONSTRUCTION FOR CS-BASED FETAL BEATS DETECTION
1. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
CompressionandBeyond
ROBUSTRECONSTRUCTIONFORCS-BASEDFETAL
BEATSDETECTION
Giulia Da Poian dapoian.giulia@spes.uniud.it
Riccardo Bernardini bernardini@uniud.it
Roberto Rinaldo rinaldo@uniud.it
University of Udine
Polytechnic Department of Engineering and Architecture
Via delle Scienze 206, Udine, Italy
See also:
http://ieeexplore.ieee.org/document/7305770/
http://www.mdpi.com/1424-8220/17/1/9/htm
2. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
ROBUSTRECONSTRUCTIONFORCS-BASEDFETALBEATSDETECTION
• We propose a novel system for the compression
and analysis of Abdominal Fetal Electrocardiogram
using Compressive Sensing (CS) and Independent
Component Analysis (ICA) applied in the
compressed domain, and sparse representations in
a specific dictionary.
• We describe the proposed scheme and a robust
variant of the Smoothed-L0 reconstruction
algorithm.
• The proposed modification significantly improves
the reconstruction quality, both for synthetic and
real-world ECG signals.
Roberto Rinaldo August 31st, 2016
3. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Roberto Rinaldo August 31st, 2016
4. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Outline
• Overview of Sparse Representations
and Compressive Sensing (CS)
• Gaussian Dictionary for ECG
approximation and CS applied to
ECG signal
• Analysis of non invasive Fetal
Electrocardiogram (fECG) - adopted
methodologies
• Reconstruction algorithm
• Results
Roberto Rinaldo August 31st, 2016
5. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Sparse Representation
coefficients
basis, frame
Many
(blue)
Sparse representation of an image via a multiscale wavelet transform
Approximation of image
obtained by keeping only the
largest 10% of the wavelet
coefficients.
A signal is sparse if most of its coefficients are (approximately) zero
Signals can often be well-approximated as a linear combination
of just a few elements from a known basis or dictionary
Roberto Rinaldo August 31st, 2016
6. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
The column vectors of a dictionary are
discrete time elementary signals called dictionary
atoms
Sparse Representation
Taking Advantage of Sparsity for:
audio/image/video
signal detection and classification
blind source separation
• compression
• denoising
• superresolution
To improve sparsity of composite signals, one has to construct a transform matrix
with the best basis
DICTIONARY: collection of elementary waveforms
or atoms or basis functions.
Example of an Overcomplete Dictionary 250
x 4267)
Roberto Rinaldo August 31st, 2016
7. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
COMPRESSIVE SENSING (CS): signals that are sparse in some
domain, can be fully reconstructed using only few random
measurements.
• Asymmetrical: Most processing at decoder
• Universality: Random measurements can be used for signals sparse in any basis
Compressive Sensing
Systems adopting compressive sensing can:
achieve sub-Nyquist sampling rates
directly acquire compressed
representations of signals
process signals and solve inference
problems in a reduced-dimensionality
domain with small or no penalties
Random Sensing
Matrix
Measurements
Roberto Rinaldo August 31st, 2016
8. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
CompressiveSensing-Reconstruction
Since M<N there are infinitely many solutions
How to solve the undetermined system of
equation to recover the original signal from the
measurements vector?
Signal reconstruction algorithm aims to find
signal’s sparse coefficient vector
NP- hard
l0 norm minimization:
can reconstruct the signal exactly
with high probability using only
M=k+1 measurements
l1 norm minimization:
can exactly recover k-sparse signals
using M=c * k log(N/K) measurements
Roberto Rinaldo August 31st, 2016
9. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Outline
• Overview of Sparse Representations
and Compressive Sensing (CS)
• Gaussian Dictionary for ECG
approximation and CS applied to
ECG signal
• Analysis of non invasive Fetal
Electrocardiogram (fECG) - adopted
methodologies
• Reconstruction algorithm
• Results
Roberto Rinaldo August 31st, 2016
10. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
GaussianDictionary
Traditional approaches use analytical
sparsifying transform (e.g. DWT, DCT, …) to
sparse represent the ECG signals
Limited Compression Ratios
Limited Reconstruction Quality
Exploit the sparsity of the ECG
signal
Study the morphology of the PQRST
cycle
Scale (Shape)
parameter
Shift parameter
Symmetric waves (Q, R and S) can be
approximated by one Gaussian function
Asymmetric waves (P or T) require 2-3
functions
Roberto Rinaldo August 31st, 2016
11. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
GaussianDictionary
Dictionary atom
Coefficient
Real ECG reconstruction examples from M=62
measurements (CR=75%)
using a sparse binary sensing matrix
Using Gaussian Dictionary
Reconstruction quality PRD=5.48%
Using Wavelets
Reconstruction quality PRD= 28.19%
Roberto Rinaldo August 31st, 2016
the RR measure metric is used, which is calculated from
the differences between matched reference RR and test RRd
intervals. This metric is denoted here by RRmeas (ms)
RRmeas =
v
u
u
t 1
I 1
I 1X
i=1
(RRi RRd
i )2, (18)
where I is the total number of fetal QRS complexes in
the reference. These measures correspond to the Physionet
Challenge scores and were obtained with the same code used
by the Challenge scorer.
Since we are applying a compression technique (CS), recon-
struction quality is evaluated using the PRD metric, defined
as
PRD(%) =
sP
n(x(n) ˆx(n))2
P
n x(n)2
⇥ 100, (19)
where, x(n) and ˆx(n) are the original (after baseline wander
removal and notch filtering) and reconstructed signals, respec-
tively. This value is computed for each reconstructed segment
of every channel and then the average value is calculated.
According to [38], reconstructions with PRD values between
0% and 2% are qualified to have “very good” quality, while
values between 2% and 9% are categorized as “good”.
Finally, we consider the total time required by the algorithm
for beat classification, including reconstruction of all the 4
channels, in order to asses the possibility to implement the
proposed framework in a real-time application. The average
time required by the algorithm, for a 1 minute long signal, is
approximately 3.7 s. The reconstruction program is written in
Matlab, running on an Intel Core i7 processor, equipped with
16 GB memory.
RESUL
FROM
THE S
Record
r01
r04
r07
r08
r10
Conce
Challe
A, i
Challe
record
have a
the di
a min
and a
predic
value
positiv
for the
respec
To
the ab
differe
compr
results
percentage root-mean-square difference
12. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
GaussianDictionary
Proposed Gaussian Dictionary
is independent from the training set
dose not require any pre-processing
Increases the compression of:
25% with respect to CS with DWT
7% with respect to BSBL-BO
Roberto Rinaldo August 31st, 2016
Bounded-block-Optimized Block Sparse Bayesian Learning (BSBL-BO)
Orthogonal Matching Pursuit (OMP)
Basis Pursuit Denoising (BPDN)
13. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Outline
• Overview of Sparse Representations
and Compressive Sensing (CS)
• Gaussian Dictionary for ECG
approximation and CS applied to
ECG signal
• Analysis of non invasive Fetal
Electrocardiogram (fECG) - adopted
methodologies
• Reconstruction algorithm
• Results
Roberto Rinaldo August 31st, 2016
14. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Abdominal fetalECG
Heart defects are among the most common birth defects and leading cause of
birth defect-related deaths
Noninvasive FECG monitoring makes use of electrodes placed on the
mother's abdomen
Recorded signals are a mixture of Maternal ECG, Fetal ECG and noise
(Respiration, EMG …)
Fetal QRSMaternal QRS
Roberto Rinaldo August 31st, 2016
15. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
CSofabdominalfetalECG
Fetal ECG recorded on the abdomen has a low SNR
5-1000 times smaller in intensity than in the adult
Less sparse than adult ECG, for example in the Wavelet domain
Reconstruction does not have to affect the interdependence relation among
the multichannel recordings
Current CS algorithms generally fail in this
application
Gaussian Dictionary can be used to increase
the performance of CS applied to fetal ECG
Roberto Rinaldo August 31st, 2016
16. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
ICAintheCSdomain
Independent Component Analysis ICA for the separation of mixed signals
(source signals are independent and have non-gaussian distributions)
We propose to perform ICA directly on the
compressed measurements
Compressed
Independent
Components
4 x m
Original mixture signal
(4 channels)
Reconstructed ICs from
ICA applied in CS domain
ICs from ICA applied on
original mixture
Abdominal
Signals
4 x N
Independent
Components
4 x N
Mixing Matrix
4 x 4
Roberto Rinaldo August 31st, 2016
17. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
BeatsClassification
Information about time and frequency location of maternal and fetal QRS
complex
The first part of the dictionary is for Maternal ECG approximation
The second part of the dictionary for Fetal ECG approximation
Classification is based on the atoms activated during reconstruction
Decomposition of IC signal in the dictionary
part related to maternal approximation
Decomposition of IC signal in the dictionary
part related to fetal approximation
Roberto Rinaldo August 31st, 2016
18. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
BeatsClassification
Detected Maternal QRS of the first
ICA signal
Detected Fetal QRS of the second ICA
signal
One more example of the proposed detection method: in red fetal beats and in green maternal
beats (on one of the 4 original signals)
Roberto Rinaldo August 31st, 2016
19. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Outline
• Overview of Sparse Representations
and Compressive Sensing (CS)
• Gaussian Dictionary for ECG
approximation and CS applied to
ECG signal
• Analysis of non invasive Fetal
Electrocardiogram (fECG) - adopted
methodologies
• Reconstruction algorithm
• Results
Roberto Rinaldo August 31st, 2016
20. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Reconstructionalgorithm
Roberto Rinaldo August 31st, 2016
• Reconstruction of the independent components is done using a modified version of the
SL0 reconstruction algorithm, introducing regularization for better immunity against
noise (D has D atoms)
random variables [2], sparse binary matrices, where has
only d non-zero randomly selected entries in each column,
have been proposed to reduce the computational cost [8]. In
this case, calculating x takes only O(dN) operations, with
a significant saving when d ⌧ N.
The SL0 algorithm proposed in [6] solves the problem in
Eq. (1) by approximating the l0-norm with a continuous func-
tion, and optimizing the resulting cost function to provide a
smooth measure of sparsity. Indeed, the l0-norm can be ap-
proximated using Gaussian functions, for small values [6],
as in
||s||S,0 , D
DX
i=1
exp( s2
i /2 2
). (2)
Thus, the minimization of the l0-norm is approximately
equivalent to maximize F (s) =
P
i exp( s2
i /2 2
). This
enables to replace the l0-norm minimization with a convex
problem, and maximize F (s) using a steepest ascent algo-
rithm. The parameter controls the trade-off between the
smoothness of the objective function and the accuracy of the
approximation of the l0-norm.
The algorithm proposed in [6] consists of two nested it-
erations, and the external loop is responsible to gradually de-
crease the value. Note that, when is sufficiently large,
exp( s2
/2 2
) ⇡ 1 s2
/2 2
, and the maximization of F (s)
ill-conditioned, th
and results in po
SL0 proposed in [
optimization prob
As in the SL0
using (2), and the
erations. The inte
feasible set {s| k
˜s = s µ k and p
min
ˆs
k ˆs
Using the Lagrang
rewritten as
min
ˆs
where is the reg
ˆs = ˜s
As for the SL0
is equal to the l2
Solving the proble
• SL0: approximate the L0 norm with the smooth function
• Problem (in the noisy case:
min
s
||s||0 s.t. As = y, A = D
F (s) =
DX
i=1
exp( s2
i /2 2
)
• Iterate decreasing ! to approach the L0 norm, and use a gradient based steepest ascend
procedure to maximize
• At each iteration, project back to the feasible set via
s s AT
(AAT
) 1
(As y)
||y As||2 ✏ )
21. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
• SL0 requires that matrix AAT is invertible, and this can be problematic with large M
(low compression ratio)
Reconstructionalgorithm
Roberto Rinaldo August 31st, 2016
• λSL0: approximate the L0 norm with the SL0 smooth function
• Iterate decreasing ! to approach the L0 norm, and use a gradient based steepest ascend
procedure to maximize
• At each iteration, project back to the feasible set
F (s)
es, where has
in each column,
onal cost [8]. In
operations, with
es the problem in
continuous func-
tion to provide a
norm can be ap-
mall values [6],
2
). (2)
is approximately
s2
i /2 2
). This
n with a convex
pest ascent algo-
-off between the
e accuracy of the
of two nested it-
ill-conditioned, then application of A†
amplifies the error
and results in poor reconstruction, even using the Robust
SL0 proposed in [9]. Introducing a regularization term in the
optimization problem enables a stable recovery of x = Ds.
As in the SL0 algorithm, we approximate the l0-norm by
using (2), and the algorithm again consists in two nested it-
erations. The internal loop seeks the maximum of F in the
feasible set {s| k y As k2 ✏}. At each step we compute
˜s = s µ k and project ˜s by solving
min
ˆs
k ˆs ˜s k2 s.t. k Aˆs y k2 ✏. (5)
Using the Lagrangian function of Eq. (5), the problem can be
rewritten as
min
ˆs
k Aˆs y k2
2 + k ˆs ˜s k2
2, (6)
where is the regularization parameter. The solution is
ˆs = ˜s AT
(AAT
+ IM ) 1
(A˜s y). (7)
As for the SL0 algorithm, for large values, the solution
ces, where has
s in each column,
ational cost [8]. In
) operations, with
ves the problem in
a continuous func-
ction to provide a
0-norm can be ap-
small values [6],
2 2
). (2)
m is approximately
( s2
i /2 2
). This
ion with a convex
epest ascent algo-
e-off between the
he accuracy of the
s of two nested it-
le to gradually de-
sufficiently large,
imization of F (s)
ill-conditioned, then application of A amplifies the error
and results in poor reconstruction, even using the Robust
SL0 proposed in [9]. Introducing a regularization term in the
optimization problem enables a stable recovery of x = Ds.
As in the SL0 algorithm, we approximate the l0-norm by
using (2), and the algorithm again consists in two nested it-
erations. The internal loop seeks the maximum of F in the
feasible set {s| k y As k2 ✏}. At each step we compute
˜s = s µ k and project ˜s by solving
min
ˆs
k ˆs ˜s k2 s.t. k Aˆs y k2 ✏. (5)
Using the Lagrangian function of Eq. (5), the problem can be
rewritten as
min
ˆs
k Aˆs y k2
2 + k ˆs ˜s k2
2, (6)
where is the regularization parameter. The solution is
ˆs = ˜s AT
(AAT
+ IM ) 1
(A˜s y). (7)
As for the SL0 algorithm, for large values, the solution
is equal to the l2 norm solution subject to k y As k2 ✏.
Solving the problem
2 2
. Let be the updated solution.
s, where has
n each column,
onal cost [8]. In
operations, with
s the problem in
ontinuous func-
ion to provide a
norm can be ap-
all values [6],
2
). (2)
s approximately
s2
i /2 2
). This
n with a convex
est ascent algo-
off between the
accuracy of the
f two nested it-
to gradually de-
ufficiently large,
ill-conditioned, then application of A†
amplifies the error
and results in poor reconstruction, even using the Robust
SL0 proposed in [9]. Introducing a regularization term in the
optimization problem enables a stable recovery of x = Ds.
As in the SL0 algorithm, we approximate the l0-norm by
using (2), and the algorithm again consists in two nested it-
erations. The internal loop seeks the maximum of F in the
feasible set {s| k y As k2 ✏}. At each step we compute
˜s = s µ k and project ˜s by solving
min
ˆs
k ˆs ˜s k2 s.t. k Aˆs y k2 ✏. (5)
Using the Lagrangian function of Eq. (5), the problem can be
rewritten as
min
ˆs
k Aˆs y k2
2 + k ˆs ˜s k2
2, (6)
where is the regularization parameter. The solution is
ˆs = ˜s AT
(AAT
+ IM ) 1
(A˜s y). (7)
As for the SL0 algorithm, for large values, the solution
is equal to the l2 norm solution subject to k y As k2 ✏.
Solving the problem
• Equivalently, solve
atrices, where has
ries in each column,
utational cost [8]. In
dN) operations, with
solves the problem in
ith a continuous func-
function to provide a
e l0-norm can be ap-
or small values [6],
s2
i /2 2
). (2)
orm is approximately
exp( s2
i /2 2
). This
zation with a convex
steepest ascent algo-
rade-off between the
d the accuracy of the
ists of two nested it-
sible to gradually de-
is sufficiently large,
aximization of F (s)
ill-conditioned, then application of A†
amplifies the error
and results in poor reconstruction, even using the Robust
SL0 proposed in [9]. Introducing a regularization term in the
optimization problem enables a stable recovery of x = Ds.
As in the SL0 algorithm, we approximate the l0-norm by
using (2), and the algorithm again consists in two nested it-
erations. The internal loop seeks the maximum of F in the
feasible set {s| k y As k2 ✏}. At each step we compute
˜s = s µ k and project ˜s by solving
min
ˆs
k ˆs ˜s k2 s.t. k Aˆs y k2 ✏. (5)
Using the Lagrangian function of Eq. (5), the problem can be
rewritten as
min
ˆs
k Aˆs y k2
2 + k ˆs ˜s k2
2, (6)
where is the regularization parameter. The solution is
ˆs = ˜s AT
(AAT
+ IM ) 1
(A˜s y). (7)
As for the SL0 algorithm, for large values, the solution
is equal to the l2 norm solution subject to k y As k2 ✏.
Solving the problem
2 2
22. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Reconstructionalgorithm
Roberto Rinaldo August 31st, 2016
equals the min-
x [3]. Therefore,
ss is usually set
n the feasible set
m, and updating
s µ , where:
(5)
he convex set to
:
). (6)
than BP, while
However, in the
thm needs to be
will propose a
orithms.
s0 = AT
(AAT
+ Im) 1
y; (12)
The proposed algorithm is summarized in 1.
Algorithm 1 -SL0
Input: µ step size, y, A, dec, min, , Kiter
Initialization: s0 AT
((AAT
) + I) 1
y,
1 = 2| max(s0)|
while k < min do
for k=1:Kiter do
s[e
s2
1
2 2
k , . . . , e
s2
K
2 2
k ]T
s s µ
Project s onto the feasible set: {s| k As y k2 ✏}
s s AT
((AAT
) + I) 1
(As y)
end for
k k dec
˜sk s
end while
Output: sOUT ˜sk
23. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Outline
• Overview of Sparse Representations
and Compressive Sensing (CS)
• Gaussian Dictionary for ECG
approximation and CS applied to
ECG signal
• Analysis of non invasive Fetal
Electrocardiogram (fECG) - adopted
methodologies
• Reconstruction algorithm
• Results
Roberto Rinaldo August 31st, 2016
24. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Results:simulatedfECG
Roberto Rinaldo August 31st, 2016
Fig. 1. Reconstruction SNR versus input SNR obtained from
100 trials for simulated fECG signals, at CR=50%, using the
SL0, SL0 and BPBN (SPGL1) algorithms using the Wavelet
and the Gaussian Dictionary.
CR
0.3 0.4 0.5 0.6 0.7 0.8
AverageReconstructionSNR[dB]
0
10
20
30
40
50
λSL0 - Gaussian Dic.
SL0 - Gaussian Dic.
BPDN - Gaussian Dic.
λSL0 - Wavelet Basis
SL0 - Wavelet Basis
BPDN - Wavelet Basis
Fig. 2. Reconstruction SNR versus CR obtained from 100 tri-
als for simulated fECG signals.
4.1. fECG Reconstruction and Fetal Beats Detection
In [7] a framework for the compression of multichannel ab-
dominal fECG and joint detection of fetal beats has been pro-
posed. The compression of the signal is based on Compres-
sive Sensing and uses a binary sparse sensing matrix, con-
taining only d = 2 ones in random positions in each column,
in order to reduce the sensor complexity [8]. Before recon-
struction using SL0, Independent Component Analysis (ICA)
3. PERFORMANCE OF SL0
section, the effect of noise on the reconstruction per-
nce is experimentally analyzed. We compare the per-
nce of the proposed algorithm with the original SL0
e BPDN-SPGL1 algorithms. The signals used in these
ments are simulated fECG signals [10] with length
256. As sparsifying dictionaries we use a dictionary
ussian like functions [7], and the Wavelet basis with
chies’ length-4 filters. The sensing matrix elements
awn as independent Gaussian random variables [2]. We
the experiment 100 times with different source signals
erent noise levels, and using each time a different ran-
SNRin [dB]
10 20 30 40 50
AverageReconstructionSNR[dB]
-10
0
10
20
30
40
50
SL0 Gaussian Dic.
λSL0 Gaussian Dic.
SL0 Wavelet Basis
λSL0 Wavelet Basis
BPDN Wavelet Basis
BPDN Gaussian Dic.
Fig. 1. Reconstruction SNR versus input SNR obtained from
Reconstruction SNR versus input
SNR obtained from 100 trials for
simulated fECG signals*, at CR=50%,
using the SL0, λSL0 and BPDN
algorithms using the Wavelet and the
Gaussian Dictionary, N=256.
Reconstruction SNR
versus CR obtained from
100 trials for simulated
fECG signals, CR=50%.
*Behar et al., “An ECG simulator for generating maternal-
foetal activity mixtures on abdominal ecg recordings,”
Physiological measurement, vol. 35, no. 8, p. 1537, 2014.
25. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Results:PhysionetChallengedatasetA*
Roberto Rinaldo August 31st, 2016
Fig. 3. Sparse decomposition of the independent component
in (a) using the SL0 algorithm, for (b) CR=75% and (c)
CR=40% and (d) using the SL0 algorithm for CR=40%. In
the graphs, different intensities represent the weight of the ac-
tivated atoms.
Compression Ratio [%]
20 40 60 80 100
AveragesensitivityS[%]
0
20
40
60
80
100
SL0
λ-SL0
(a)
Compression Ratio [%]
20 40 60 80 100
AveragePRD[%]
0
10
20
30 SL0
λ-SL0
(b)
Fig. 4. (a) Detection performance for SL0 and SL0 algo-
rithm. The vertical coordinate gives the average Sensitivity
for dataset A at different CR values. (b) Comparison of aver-
age PRD when using the two algorithms at different CRs.
As an example, we show in Fig. 3 (a) a portion of the IC of
the expe
matrix (
badly an
value is
that the
almost i
at lower
In Fig. 4
outperfo
struction
4.2. Infl
In this s
tion pro
ent sens
variable
not theo
non-zero
imentall
(a) Detection performance for SL0 and λSL0 algorithm.The
vertical coordinate gives the average Sensitivity for dataset
A at different CR values. (b) Comparison of average PRD
when using the two algorithms at different CRs.
e, a second
pending on
recordings.
ks of length
, with only
position is
particularly
an efficient
we consider
M = 62
o CR=75%.
7 additions.
sed on the
hat it is the
quality of
, in Section
framework
ed with 16
signal ICs
ese can be
xing matrix
work we use
e Smoothed
performance figures usually applied for the assessment of QRS
detection algorithms, i.e., sensitivity (S) and positive predic-
tivity (P+). According to the American National Standard [36]
S and P+ are computed as
S =
TP
TP + FN
100, P+ =
TP
TP + FP
100, (15)
where TP is the number of true positives, FP of false positives
and FN of false negatives. A detected beat is considered to be
true positive if its time location differs less than 50 ms from
the reference markers (within a window of 100 ms centered
on the reference marker). The algorithm accuracy can be also
evaluated using the F1 measure, proposed in [37],
F1 = 2
S P+
S + P+
100 = 2
TP
2TP + FN + FP
100. (16)
Additionally, we apply the scoring methods proposed in
[4], using two metrics, i.e., fetal heart rate measurement and
RR interval measurement. The first one, denoted here as
HRmeas (bpm2
), is used to assess the ability of the algorithm
to provide valid fHR estimation. It is based on the squared
difference between matched reference (fHR) and detected
fHRd
measurements every 5 s (12 instances for 1 min long
signals)
HRmeas =
1
12
12X
(fHRi fHRd
i )2
. (17)
We repeat the experiment 20 times with different random
sparse binary matrix (d = 2), for all the signals in dataset A.
The reported values are the average of these simulations.
*“Physionet challenge 2013,” http: www.physionet.org/challenge/2013/.
26. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Results:sensingmatrix
Roberto Rinaldo August 31st, 2016
Table 1. Average performance of detection and reconstruction
for SL0 and SL0 for dataset A.
SL0 SL0
CR S PRD S PRD
% [%] [%] [%] [%]
40 Sparse 2 46 5.27 85 3.77
Gaussian 45 5.58 84 3.72
50 Sparse 2 77 5.93 85 4.49
Gaussian 75 5.71 85 4.27
75 Sparse 2 84 8.81 84 8.14
Gaussian 84 8.80 84 8.02
retical reconstruction performance for i.i.d. Gaussian sensing
matrices is well established, we can see experimentally that,
for the class of signals we are considering, sparse matrices
have similar performance. The use of a sparse sensing matrix
with d = 2 allows to achieve almost identical reconstruc-
tion results, besides the very low complexity implementation.
Finally, Table 1 summarizes the average reconstruction and
can efficie
beats in th
ratios. Mo
ing matric
compares
permitting
[1] D. L
ory,
1306
[2] E. J
ceed
cian
[3] D. C
sign
IEEE
[4] G. D
Average performance of detection and
reconstruction for SL0 and λSL0 for dataset A.
27. UNIVERSITY OF UDINE – ITALY – DPIA Eusipco 2016, Budapest www.uniud.it
Conclusions
The proposed method has been tested on public datasets (set A and set B of
the Physionet Challenge, Silesia dataset*), showing promising results for both
reconstruction quality and detection/classification performance
The use of the proposed λSL0 reconstruction algorithm is crucial for
consistent performance at all compression ratios
Experiments show an average reconstruction time for the λSL0 algorithm
ranging from 0.07 s, when CR=30%, to 0.01 s, when CR=80%. Thus, it
maintains approximately the same computational cost of the original SL0
algorithm (ranging from 0.03 s to 0.01 s), while being much faster than the
BPDN algorithm (1.6 s to 0.6 s). Programs are written in Matlab, running on an
Intel Core i7 processor, equipped with 16 GB memory.
The proposed framework has good performance and is suitable for real-time
implementation with low-power sensors and low complexity devices.
Roberto Rinaldo August 31st, 2016
*A. L. Goldberger, L. A. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C.-K. Peng, and H. E.
Stanley, “Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals,” Circulation, vol.
101, no. 23, pp. e215–e220, 2000.