The document provides an introduction to the perceptron model. It discusses how the perceptron was originally invented in 1958 as a machine for image recognition, with an array of photocells randomly connected to neurons. Weights were encoded using potentiometers, and weight updates during learning were performed by electric motors. It then discusses how multiple perceptrons can be combined to solve non-linearly separable problems like XOR. Finally, it provides details on perceptron weight calculation and the use of an activation function to produce the output in a nonlinear way similar to biological neurons.
This document discusses problems involving modulation techniques and signal detection. Problem 1 asks to sketch modulated waves for 8-ary ASK, 4-ary PSK, and 4-ary FSK modulation of a binary sequence. Problem 2 provides a formula for probability of error for 4-ary PAM and asks to calculate average power. Problem 3 does similarly for 4-ary QAM. Problem 4 describes a binary system with an integrate-and-dump detector and asks to analyze the detector and find minimum error probability.
1. The Fourier transform allows signals to be represented and analyzed in the frequency domain by decomposing them into their constituent frequencies.
2. For periodic signals, the Fourier transform results in a discrete spectrum, while for non-periodic signals it yields a continuous spectrum.
3. The continuous time Fourier transform (CTFT) represents a non-periodic signal as an integral that expresses the signal as a sum of complex exponentials oscillating at all possible frequencies.
Design and Implementation of Low Ripple Low Power Digital Phase-Locked LoopCSCJournals
We propose a phase-locked loop (PLL) architecture, which reduces the double frequency ripple without increasing the order of loop filter. Proposed architecture uses quadrature numerically–controlled oscillator (NCO) to provide two output signals with phase difference of π/2. One of them is subtracted from the input signal before multiplying with the other output of NCO. The system also provides stability in case the input signal has noise in amplitude or phase. The proposed structure is implemented using field programmable gate array (FPGA), which dissipates 15.44mw and works at clock frequency of 155.8 MHz.
The document discusses intersymbol interference (ISI) in baseband data transmission. ISI arises from deviations in a communication channel's frequency response from ideal, causing received pulses to be affected by neighboring pulses. This can be mitigated by matched filtering to maximize signal-to-noise ratio or by controlling the received pulse shape when noise is negligible. ISI causes the sampled output to depend on neighboring transmitted bits. Distortionless transmission requires designing transmit and receive filters such that only the desired bit contributes to the sampled output.
The document describes an experiment to verify the Nyquist sampling theorem using MATLAB. It discusses sampling a continuous time signal at frequencies below, equal to, and above twice the maximum frequency of the signal. The results show aliasing when sampling below the Nyquist rate, no aliasing when sampling at the Nyquist rate, and perfect reconstruction when sampling above the Nyquist rate. The experiment generates a sinusoidal signal, samples it at different rates, and plots the discrete and reconstructed continuous signals to demonstrate the sampling theorem.
Single Electron Spin Detection Slides For Uno Interviewchenhm
1. The document discusses different algorithms for detecting weak electron spin signals in single electron spin microscopy, including energy detector, matched filter, power-law detector, M-quadratic detector, and generalized likelihood ratio detector.
2. Simulation results show that detection performance improves with more prior knowledge of the signal characteristics, and the M-quadratic detector achieves better performance than the energy detector with lower computation time.
3. Future work involves developing optimal quadratic detection schemes and implementing the algorithms on a computer cluster for real-time signal detection.
The document provides an introduction to the perceptron model. It discusses how the perceptron was originally invented in 1958 as a machine for image recognition, with an array of photocells randomly connected to neurons. Weights were encoded using potentiometers, and weight updates during learning were performed by electric motors. It then discusses how multiple perceptrons can be combined to solve non-linearly separable problems like XOR. Finally, it provides details on perceptron weight calculation and the use of an activation function to produce the output in a nonlinear way similar to biological neurons.
This document discusses problems involving modulation techniques and signal detection. Problem 1 asks to sketch modulated waves for 8-ary ASK, 4-ary PSK, and 4-ary FSK modulation of a binary sequence. Problem 2 provides a formula for probability of error for 4-ary PAM and asks to calculate average power. Problem 3 does similarly for 4-ary QAM. Problem 4 describes a binary system with an integrate-and-dump detector and asks to analyze the detector and find minimum error probability.
1. The Fourier transform allows signals to be represented and analyzed in the frequency domain by decomposing them into their constituent frequencies.
2. For periodic signals, the Fourier transform results in a discrete spectrum, while for non-periodic signals it yields a continuous spectrum.
3. The continuous time Fourier transform (CTFT) represents a non-periodic signal as an integral that expresses the signal as a sum of complex exponentials oscillating at all possible frequencies.
Design and Implementation of Low Ripple Low Power Digital Phase-Locked LoopCSCJournals
We propose a phase-locked loop (PLL) architecture, which reduces the double frequency ripple without increasing the order of loop filter. Proposed architecture uses quadrature numerically–controlled oscillator (NCO) to provide two output signals with phase difference of π/2. One of them is subtracted from the input signal before multiplying with the other output of NCO. The system also provides stability in case the input signal has noise in amplitude or phase. The proposed structure is implemented using field programmable gate array (FPGA), which dissipates 15.44mw and works at clock frequency of 155.8 MHz.
The document discusses intersymbol interference (ISI) in baseband data transmission. ISI arises from deviations in a communication channel's frequency response from ideal, causing received pulses to be affected by neighboring pulses. This can be mitigated by matched filtering to maximize signal-to-noise ratio or by controlling the received pulse shape when noise is negligible. ISI causes the sampled output to depend on neighboring transmitted bits. Distortionless transmission requires designing transmit and receive filters such that only the desired bit contributes to the sampled output.
The document describes an experiment to verify the Nyquist sampling theorem using MATLAB. It discusses sampling a continuous time signal at frequencies below, equal to, and above twice the maximum frequency of the signal. The results show aliasing when sampling below the Nyquist rate, no aliasing when sampling at the Nyquist rate, and perfect reconstruction when sampling above the Nyquist rate. The experiment generates a sinusoidal signal, samples it at different rates, and plots the discrete and reconstructed continuous signals to demonstrate the sampling theorem.
Single Electron Spin Detection Slides For Uno Interviewchenhm
1. The document discusses different algorithms for detecting weak electron spin signals in single electron spin microscopy, including energy detector, matched filter, power-law detector, M-quadratic detector, and generalized likelihood ratio detector.
2. Simulation results show that detection performance improves with more prior knowledge of the signal characteristics, and the M-quadratic detector achieves better performance than the energy detector with lower computation time.
3. Future work involves developing optimal quadratic detection schemes and implementing the algorithms on a computer cluster for real-time signal detection.
The document analyzes a method for comparing two audio files to detect human errors using fast Fourier transforms (FFT). It describes using FFT to convert audio files from the time domain to the frequency domain. It then calculates the mean squared error (MSE) between the normalized spectral densities of the two files. A low MSE would indicate the files are identical, while a higher MSE shows a difference. The document provides the steps and flowchart used, and includes examples of Matlab and Labview code implementing the comparison method on identical and non-identical audio files.
Environmentally robust ASR front end for DNN-based acoustic modelsTakuya Yoshioka
The individual and combined impacts of various front-end approaches on the performance of deep neural network (DNN) based speech recognition systems are examined in distant talking situations. The contents were published in:
Takuya Yoshioka and Mark J. F. Gales, "Environmentally robust ASR front-end for deep neural network acoustic models," Computer Speech and Language, vol. 31, no. 1, pp. 65-86, May 2015.
The document discusses Fast Fourier Transform (FFT) analysis. It begins by explaining what Fourier Transform and Discrete Fourier Transform (DFT) are and how they convert signals from the time domain to the frequency domain. It then states that FFT is an efficient algorithm for performing DFT, allowing it to be done much faster on computers. The document proceeds to describe different types of FFT algorithms like Cooley-Tukey, Prime Factor, Bruun's, and Rader's algorithms. It concludes by discussing characteristics of FFT like approximation, accuracy, and complexity bounds, as well as applications and how FFT can be used to analyze vibration signals in the frequency domain.
The receiver structure consists of four main components:
1. A matched filter that maximizes the SNR by matching the source impulse and channel.
2. An equalizer that removes intersymbol interference.
3. A timing component that determines the optimal sampling time using an eye diagram.
4. A decision component that determines whether the received bit is a 0 or 1 based on a threshold.
The performance of the receiver depends on factors like noise, equalization technique used, and timing accuracy. The bit error rate can be estimated using tools like error functions.
The document analyzes a method for comparing two audio files using the Fast Fourier Transform (FFT) algorithm to detect human errors. It describes how the FFT works, breaking signals into frames and returning frequency values. It then outlines the steps to compare audio files, including truncating signals to equal lengths, calculating normalized energy spectral density from the FFTs, and computing the mean-square-error between the signals. MATLAB and LabVIEW code examples are provided to load files, perform the FFT, calculate MSE, and display results identifying whether files are identical or not. Graphs show FFT results and cross-correlations for identical and non-identical file pairs.
This document discusses correlative-level coding and its applications in baseband pulse transmission systems. Correlative-level coding introduces controlled intersymbol interference to increase signaling rate. It allows partial response signaling and maximum likelihood detection at the receiver. Specific techniques discussed include duobinary signaling and modified duobinary signaling. The document also covers tapped-delay line equalization using adaptive algorithms like least mean square to compensate for channel distortion. Decision feedback equalization and its implementation are summarized as well. Eye patterns are described as a tool to evaluate signal quality in such systems.
This document discusses techniques for pulse shaping to reduce inter-symbol interference (ISI) in digital communication systems. It introduces the Nyquist criteria that pulse shapes must satisfy to avoid ISI, including having zero crossings at symbol intervals, zero areas within symbol periods, and zero values at decision thresholds. Methods like raised cosine filtering are presented that trade off bandwidth for smoothness to meet the Nyquist criteria. The document also discusses partial response signaling techniques like duobinary that relax the criteria but require differential encoding to avoid error propagation.
This document describes an experiment using Matlab to represent and manipulate signals. It outlines various tasks for students to complete, including sampling signals, analyzing aliasing, visualizing signals using different commands, generating non-periodic and periodic signals like sinusoids, square waves and sawtooth waves. Students are instructed to write code, make observations, and include specific sections in their report.
Implementing 3D SPHARM Surfaces Registration on Cell B.E. ProcessorPTIHPA
This document describes implementing 3D SPHARM surface registration on a Cell processor. It discusses SPHARM expansion and registration, calculating rotation coefficients, root mean square distance, and implementations in Matlab and on the Cell processor. The Cell implementation uses loop fusion, lookup tables, and optimizations for the Cell architecture like vectorization and data alignment. Performance analysis shows a dramatic increase in speed on the Cell due to its architecture and algorithm optimizations. Care is needed for data placement and transfer due to limited local store.
The document discusses problems related to analogue and digital communications. It contains 5 problems:
1) Drawing the spectrum of a message signal sampled at different rates and specifying the cutoff frequency to fully recover the original signal from its sampled version.
2) Sketching the resulting pulse code modulation (PCM) wave for one cycle of an input signal that is quantized using a 4-bit binary system.
3) Determining the number of quantizing levels, quantizer step size, average quantizing noise power, and output signal-to-noise ratio for a sinusoidal modulating wave quantized using an n-bit code word.
4) Finding the Nyquist sampling rate for two signals.
The discrete Fourier transform has many applications in science and engineering. For example, it is often used in digital signal processing applications such as voice recognition and image processing.
3.Frequency Domain Representation of Signals and SystemsINDIAN NAVY
This document provides an overview of frequency domain representation of signals and systems. It defines key concepts such as the Fourier transform, which converts a signal from the time domain to the frequency domain. The frequency spectrum shows the distribution of frequencies within a signal. Periodic signals can be represented using Fourier series, while aperiodic signals use the Fourier transform. Properties of the Fourier transform such as linearity, time shifting, and the convolution theorem are also covered.
1. The document discusses Fourier transforms of discrete signals and sampling theory. It explains that continuous signals are digitized through sampling and the discrete time Fourier transform (DTFT) can be used to find the frequency spectrum of discrete signals.
2. It also covers the discrete Fourier transform (DFT) which is used when only a finite amount of data is available. The DFT breaks up a signal into its constituent frequencies.
3. Fast Fourier transform (FFT) algorithms like the radix-2 algorithm improve the efficiency of computing the DFT and allow it to be done in O(NlogN) time rather than O(N2) time.
Symica is an electronic design automation tool for analog and mixed-signal integrated circuit design. It supports hierarchical design entry and compatibility with popular simulation models. Symica has capabilities for modern IC development including accommodating different process design kits. Its affordable and flexible pricing makes it attractive for startups and independent researchers. Established semiconductor companies can use Symica as a cost-saving solution for expanding design capabilities beyond limited licenses from major EDA vendors.
Gene's law, Common gate, kernel Principal Component Analysis, ASIC Physical Design Post-Layout Verification, TSMC180nm, 0.13um IBM CMOS technology, Cadence Virtuoso, FPAA, in Spanish, Bruun E,
The Tektronix MDO3104 is a mixed domain oscilloscope with 1 GHz analog bandwidth and built-in spectrum analyzer, arbitrary function generator, logic analyzer, and protocol analyzer. It offers 4 analog channels, 16 digital channels, and 1 RF input channel. The MDO3104 also supports a variety of serial protocols and comes with various optional application modules for extended analysis capabilities.
Low power sar ad cs presented by pieter harpeHoopeer Hoopeer
The document discusses the operation and design tradeoffs of SAR and sigma-delta analog-to-digital converters (ADCs). It explains that SAR ADCs use a binary search approach to determine each output bit but are limited by noise and nonlinearity issues from components like track-and-hold switches and digital-to-analog converters. Sigma-delta ADCs shift quantization noise out of band through oversampling and noise shaping to achieve high resolution without requiring high-precision analog components. The document also covers speed limitations of SAR ADCs and how power consumption scales with resolution for different blocks like comparators and logic.
Lab 2: Cadence Tutorial on Layout and DRC/LVS/PEX
This section describes how to extract a netlist from your layout that includes parasitic resistances and capacitances. You will then be able to re-simulate your design with extracted parasitics in Spectre. PEX requires a clean LVS so that extracted parasitics can be correlated to nets on the schematic. Initiate the PEX interface by clicking on:Calibre > Run PEX
A window asking to load a runset file will now appear. Browse to the file
Step by step process of uploading presentation videos Hoopeer Hoopeer
Deep neural network, compressive sensing, floating gate techniques can be efficiently employed to increase voltage swing and reduce supply voltage requirements of class AB regulated cascode current mirrors, implement extreme low power analog circuits with this process. /also have good references for subthreshold region.
[Extreme Low Power Differential Pair: An Experimental Evaluation, Super-Gain-Boosted Miller Op-Amp based on Nested Regulated Cascode Techniques , Step by Step process of uploading presentation videos, Dennis Ritchie The creator of the C programming language and co-creator of Unix
This document is a project report submitted by Renu Gupta to fulfill requirements for a Master's degree in Electronics and Communication Engineering. The project involves realizing various signal processing and generating circuits using an Operational Trans-Resistance Amplifier (OTRA). The OTRA is implemented using commercially available CFOA ICs. Circuits designed include filters, oscillators, and an active inductor-based LC oscillator. Theoretical results are verified through PSPICE simulations and experiments using practical circuits assembled with CFOA ICs. The report documents the work conducted under the guidance of Dr. Neeta Pandey.
S-parameters are used to analyze microwave circuits operating between 300MHz to 1000GHz. S-parameters relate the input and output traveling wave variables of network components using a scattering matrix. For a two-port network, the S-parameters relate the incident and reflected waves at each port. S11 and S22 represent reflection coefficients, while S12 and S21 represent transmission coefficients. Networks can be reciprocal if S12 = S21, and symmetrical if S11 = S22. LTSpice can be used to simulate S-parameters for two-port networks.
The document analyzes a method for comparing two audio files to detect human errors using fast Fourier transforms (FFT). It describes using FFT to convert audio files from the time domain to the frequency domain. It then calculates the mean squared error (MSE) between the normalized spectral densities of the two files. A low MSE would indicate the files are identical, while a higher MSE shows a difference. The document provides the steps and flowchart used, and includes examples of Matlab and Labview code implementing the comparison method on identical and non-identical audio files.
Environmentally robust ASR front end for DNN-based acoustic modelsTakuya Yoshioka
The individual and combined impacts of various front-end approaches on the performance of deep neural network (DNN) based speech recognition systems are examined in distant talking situations. The contents were published in:
Takuya Yoshioka and Mark J. F. Gales, "Environmentally robust ASR front-end for deep neural network acoustic models," Computer Speech and Language, vol. 31, no. 1, pp. 65-86, May 2015.
The document discusses Fast Fourier Transform (FFT) analysis. It begins by explaining what Fourier Transform and Discrete Fourier Transform (DFT) are and how they convert signals from the time domain to the frequency domain. It then states that FFT is an efficient algorithm for performing DFT, allowing it to be done much faster on computers. The document proceeds to describe different types of FFT algorithms like Cooley-Tukey, Prime Factor, Bruun's, and Rader's algorithms. It concludes by discussing characteristics of FFT like approximation, accuracy, and complexity bounds, as well as applications and how FFT can be used to analyze vibration signals in the frequency domain.
The receiver structure consists of four main components:
1. A matched filter that maximizes the SNR by matching the source impulse and channel.
2. An equalizer that removes intersymbol interference.
3. A timing component that determines the optimal sampling time using an eye diagram.
4. A decision component that determines whether the received bit is a 0 or 1 based on a threshold.
The performance of the receiver depends on factors like noise, equalization technique used, and timing accuracy. The bit error rate can be estimated using tools like error functions.
The document analyzes a method for comparing two audio files using the Fast Fourier Transform (FFT) algorithm to detect human errors. It describes how the FFT works, breaking signals into frames and returning frequency values. It then outlines the steps to compare audio files, including truncating signals to equal lengths, calculating normalized energy spectral density from the FFTs, and computing the mean-square-error between the signals. MATLAB and LabVIEW code examples are provided to load files, perform the FFT, calculate MSE, and display results identifying whether files are identical or not. Graphs show FFT results and cross-correlations for identical and non-identical file pairs.
This document discusses correlative-level coding and its applications in baseband pulse transmission systems. Correlative-level coding introduces controlled intersymbol interference to increase signaling rate. It allows partial response signaling and maximum likelihood detection at the receiver. Specific techniques discussed include duobinary signaling and modified duobinary signaling. The document also covers tapped-delay line equalization using adaptive algorithms like least mean square to compensate for channel distortion. Decision feedback equalization and its implementation are summarized as well. Eye patterns are described as a tool to evaluate signal quality in such systems.
This document discusses techniques for pulse shaping to reduce inter-symbol interference (ISI) in digital communication systems. It introduces the Nyquist criteria that pulse shapes must satisfy to avoid ISI, including having zero crossings at symbol intervals, zero areas within symbol periods, and zero values at decision thresholds. Methods like raised cosine filtering are presented that trade off bandwidth for smoothness to meet the Nyquist criteria. The document also discusses partial response signaling techniques like duobinary that relax the criteria but require differential encoding to avoid error propagation.
This document describes an experiment using Matlab to represent and manipulate signals. It outlines various tasks for students to complete, including sampling signals, analyzing aliasing, visualizing signals using different commands, generating non-periodic and periodic signals like sinusoids, square waves and sawtooth waves. Students are instructed to write code, make observations, and include specific sections in their report.
Implementing 3D SPHARM Surfaces Registration on Cell B.E. ProcessorPTIHPA
This document describes implementing 3D SPHARM surface registration on a Cell processor. It discusses SPHARM expansion and registration, calculating rotation coefficients, root mean square distance, and implementations in Matlab and on the Cell processor. The Cell implementation uses loop fusion, lookup tables, and optimizations for the Cell architecture like vectorization and data alignment. Performance analysis shows a dramatic increase in speed on the Cell due to its architecture and algorithm optimizations. Care is needed for data placement and transfer due to limited local store.
The document discusses problems related to analogue and digital communications. It contains 5 problems:
1) Drawing the spectrum of a message signal sampled at different rates and specifying the cutoff frequency to fully recover the original signal from its sampled version.
2) Sketching the resulting pulse code modulation (PCM) wave for one cycle of an input signal that is quantized using a 4-bit binary system.
3) Determining the number of quantizing levels, quantizer step size, average quantizing noise power, and output signal-to-noise ratio for a sinusoidal modulating wave quantized using an n-bit code word.
4) Finding the Nyquist sampling rate for two signals.
The discrete Fourier transform has many applications in science and engineering. For example, it is often used in digital signal processing applications such as voice recognition and image processing.
3.Frequency Domain Representation of Signals and SystemsINDIAN NAVY
This document provides an overview of frequency domain representation of signals and systems. It defines key concepts such as the Fourier transform, which converts a signal from the time domain to the frequency domain. The frequency spectrum shows the distribution of frequencies within a signal. Periodic signals can be represented using Fourier series, while aperiodic signals use the Fourier transform. Properties of the Fourier transform such as linearity, time shifting, and the convolution theorem are also covered.
1. The document discusses Fourier transforms of discrete signals and sampling theory. It explains that continuous signals are digitized through sampling and the discrete time Fourier transform (DTFT) can be used to find the frequency spectrum of discrete signals.
2. It also covers the discrete Fourier transform (DFT) which is used when only a finite amount of data is available. The DFT breaks up a signal into its constituent frequencies.
3. Fast Fourier transform (FFT) algorithms like the radix-2 algorithm improve the efficiency of computing the DFT and allow it to be done in O(NlogN) time rather than O(N2) time.
Symica is an electronic design automation tool for analog and mixed-signal integrated circuit design. It supports hierarchical design entry and compatibility with popular simulation models. Symica has capabilities for modern IC development including accommodating different process design kits. Its affordable and flexible pricing makes it attractive for startups and independent researchers. Established semiconductor companies can use Symica as a cost-saving solution for expanding design capabilities beyond limited licenses from major EDA vendors.
Gene's law, Common gate, kernel Principal Component Analysis, ASIC Physical Design Post-Layout Verification, TSMC180nm, 0.13um IBM CMOS technology, Cadence Virtuoso, FPAA, in Spanish, Bruun E,
The Tektronix MDO3104 is a mixed domain oscilloscope with 1 GHz analog bandwidth and built-in spectrum analyzer, arbitrary function generator, logic analyzer, and protocol analyzer. It offers 4 analog channels, 16 digital channels, and 1 RF input channel. The MDO3104 also supports a variety of serial protocols and comes with various optional application modules for extended analysis capabilities.
Low power sar ad cs presented by pieter harpeHoopeer Hoopeer
The document discusses the operation and design tradeoffs of SAR and sigma-delta analog-to-digital converters (ADCs). It explains that SAR ADCs use a binary search approach to determine each output bit but are limited by noise and nonlinearity issues from components like track-and-hold switches and digital-to-analog converters. Sigma-delta ADCs shift quantization noise out of band through oversampling and noise shaping to achieve high resolution without requiring high-precision analog components. The document also covers speed limitations of SAR ADCs and how power consumption scales with resolution for different blocks like comparators and logic.
Lab 2: Cadence Tutorial on Layout and DRC/LVS/PEX
This section describes how to extract a netlist from your layout that includes parasitic resistances and capacitances. You will then be able to re-simulate your design with extracted parasitics in Spectre. PEX requires a clean LVS so that extracted parasitics can be correlated to nets on the schematic. Initiate the PEX interface by clicking on:Calibre > Run PEX
A window asking to load a runset file will now appear. Browse to the file
Step by step process of uploading presentation videos Hoopeer Hoopeer
Deep neural network, compressive sensing, floating gate techniques can be efficiently employed to increase voltage swing and reduce supply voltage requirements of class AB regulated cascode current mirrors, implement extreme low power analog circuits with this process. /also have good references for subthreshold region.
[Extreme Low Power Differential Pair: An Experimental Evaluation, Super-Gain-Boosted Miller Op-Amp based on Nested Regulated Cascode Techniques , Step by Step process of uploading presentation videos, Dennis Ritchie The creator of the C programming language and co-creator of Unix
This document is a project report submitted by Renu Gupta to fulfill requirements for a Master's degree in Electronics and Communication Engineering. The project involves realizing various signal processing and generating circuits using an Operational Trans-Resistance Amplifier (OTRA). The OTRA is implemented using commercially available CFOA ICs. Circuits designed include filters, oscillators, and an active inductor-based LC oscillator. Theoretical results are verified through PSPICE simulations and experiments using practical circuits assembled with CFOA ICs. The report documents the work conducted under the guidance of Dr. Neeta Pandey.
S-parameters are used to analyze microwave circuits operating between 300MHz to 1000GHz. S-parameters relate the input and output traveling wave variables of network components using a scattering matrix. For a two-port network, the S-parameters relate the incident and reflected waves at each port. S11 and S22 represent reflection coefficients, while S12 and S21 represent transmission coefficients. Networks can be reciprocal if S12 = S21, and symmetrical if S11 = S22. LTSpice can be used to simulate S-parameters for two-port networks.
Influential and powerful professional electrical and electronics engineering ...Hoopeer Hoopeer
powerful professional electrical and electronics engineering books
. Analysis and Design of Analog Integrated Circuits
Analysis and Design of Analog Integrated Circuits
Analog filter design
This document provides instructions for assembling and operating a 3-stage FM transmitter kit. It includes a list of components, descriptions of each circuit stage including amplification, oscillation and tuning, and guidance on assembling, powering and tuning the transmitter to broadcast within the FM radio band. The transmitter is designed to transmit audio from a microphone up to 1 km when powered by a 9V battery and connected to an antenna.
The Teager Energy Operator (TEO) is a feature extraction circuit used for electroencephalography (EEG) signals. TEO uses a low-pass filter and multiplier to measure instantaneous energy, which can help classify specific sleep stages. TEO is designed using a mathematical formula and extracts features from EEG signals by measuring energy. It is one tool among others, including signal level detection and peak detection, that can extract features from EEG, electromyography, and electrooculography signals.
The document provides information about the Department of Physics at the University of Patras in Greece. It includes details such as the chairperson, degrees offered, faculty members, laboratories, courses, and research activities. The department has over 1200 undergraduate students and 70 graduate students. There are 50 faculty members across four divisions conducting teaching and research in various fields of physics.
The document provides 15 links to YouTube videos and one link to a PDF file featuring lectures on various topics. The YouTube videos range in length from 15 minutes to over an hour and cover subjects such as Islamic theology, philosophy and spirituality. The linked PDF file is a condensed nightly prayer handbook.
1. The document provides instructions on how to generate a layout view in Cadence Virtuoso and perform layout verification and simulation with extracted parasitics. It describes creating a CMOS inverter layout including placing nFET and pFET devices and connecting their terminals.
2. Key layers used in the layout are described, including Metal 1 (M1), Poly (PC), Diffusion (RX), Contact (CA), N-well (NW), P+ implant (BP), and Via 1 (V1). Design rules for spacing and dimensions are outlined.
3. An example inverter layout is shown, and instructions are provided on how to move and edit devices, enter layout shapes, and connect the devices to
The document discusses various performance evaluation metrics that are commonly used to evaluate classification algorithms and predictive models, including accuracy, precision, recall, F1 score, confusion matrix, receiver operating characteristic curve, and precision-recall curve. It provides definitions and formulas for calculating each of these metrics and discusses their strengths and weaknesses for evaluating model performance, especially for imbalanced datasets. Examples of each metric are given from literature on applications like seizure detection, trust prediction in social networks, and gene association networks. Feature extraction techniques for biomedical signals like EEG are also mentioned.
BJT and MOS, Advanced Circuit Topologies, concept of tracking, mm-Wave frequency beyond 30GHz, Bandgap is a stable, well defined, and constant current source
This document provides an overview of VLSI-compatible implementations for artificial neural networks. It begins with an introduction and motivation for the work. The objectives are to develop generalized artificial neural network models and architectures that can be implemented using standard VLSI technologies. Various hardware implementation techniques for neural networks are reviewed, including pulse-coded, digital, and analog approaches. Different analog implementations like resistive synaptic weights, switched capacitor neurons, current-mode and sub-threshold designs are discussed. The document concludes with a comparison of some existing neural network hardware systems and a summary of the chapter.
William Strange earned his PhD in 1959 from the University of California, Los Angeles under advisor Peter Henrici. His thesis was titled "Difference Methods for Mixed Boundary Value Problems". One of his PhD students was Hermann Flaschka.
Professor Dr. Abdullah Alison was originally named Arthur Ellison, a British electrical engineer who converted to Islam. In 1974, he initiated and inaugurated the first International Conference on Electrical Machines, known as ICEM. After embracing Islam, his name became Professor Dr. Abdullah Alison and he worked to advance electrical engineering and share knowledge across international borders until his death in 2000.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Gas agency management system project report.pdfKamal Acharya
The project entitled "Gas Agency" is done to make the manual process easier by making it a computerized system for billing and maintaining stock. The Gas Agencies get the order request through phone calls or by personal from their customers and deliver the gas cylinders to their address based on their demand and previous delivery date. This process is made computerized and the customer's name, address and stock details are stored in a database. Based on this the billing for a customer is made simple and easier, since a customer order for gas can be accepted only after completing a certain period from the previous delivery. This can be calculated and billed easily through this. There are two types of delivery like domestic purpose use delivery and commercial purpose use delivery. The bill rate and capacity differs for both. This can be easily maintained and charged accordingly.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Generative AI Use cases applications solutions and implementation.pdfmahaffeycheryld
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Software Engineering and Project Management - Software Testing + Agile Method...Prakhyath Rai
Software Testing: A Strategic Approach to Software Testing, Strategic Issues, Test Strategies for Conventional Software, Test Strategies for Object -Oriented Software, Validation Testing, System Testing, The Art of Debugging.
Agile Methodology: Before Agile – Waterfall, Agile Development.
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...PIMR BHOPAL
Variable frequency drive .A Variable Frequency Drive (VFD) is an electronic device used to control the speed and torque of an electric motor by varying the frequency and voltage of its power supply. VFDs are widely used in industrial applications for motor control, providing significant energy savings and precise motor operation.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
1. Teager Energy Operator
(TEO)
is a feature extraction circuit for EEG
For EEG:
BPF: for classification of specific sleep
stage. TEO: for feature classification
measurements, consisting of LPF and
multiplier. The later is used to
measure instantaneous energy.
TEO is designed by:
ψ x t =
dx(t)
dt
2
− x t
d2
x t
dt2
ψ x[n] = xn
2 − xn+1xn−1
Feature extraction measurements for
EXG signals: 1. TEO operator for EEG
2. Signal level detector for EMG
3. Signal peak detector for EOG
CF.: Wearable Multi-Biosignal Analysis Integrated Interface with the Direct Sleep
Stage Classification
AFE BPF TEO
EEG
LPF
Comparator
x2
Normalization
Digital output
LPF LPF x
x
Σ
Band Pass
Filtered
EEG