A Review Of Adaptive Technique For Image Super Resolution

A Review Of Adaptive Technique For Image Super Resolution
A Review of Adaptive Technique for Image Super–resolution
Prof. S. P. Bhosale
Assistant Professor , Department of electronics,
A.I.S.S.M.S COE, Pune, India spbhosale@aisssmscoe.com ABSTRACT
Increase in resolution of image has been one driving factor in the development and progress of the
ﬁelds related to the capture, processing and display of digital images and video. Number of authors
has carried out research on various techniques on super–resolution algorithms which are classified
into two basic categories: 'single–frame super resolution' and the more common 'multi–frame super
resolution'. Single frame super–resolution is a very ill–posed problem due to the lack of any new
additional information. Multi–frame Super resolution on the other hand presents more information
in the form of Low Resolution (LR) frames that are displaced from each other making it a more
tractable problem. A related problem to super Resolution (SR) techniques is image restoration,
which is well established area in image processing application. An other problem related to SR
reconstruction is image interpolation that has been used to increase the size of a single image.
Keywords
Adaptive technique, super resolution technique, frequency domain method.
1. INTRODUCTION
A demand for higher resolution is seen in many discipline including bio–medical imaging, satellite
and astronomical imaging, chemical and military surveillance and remote sensing. But the current
state of image sensor
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Controlling Robot With Speech Recognition
A MAJOR PROJECT REPORT ON CONTROLLING ROBOT WITH SPEECH RECOGNITION
SUBMITTED IN PARTIAL FULFILLMENT OF THE DEGREE BACHELOR IN TECHNOLOGY
OF ELECTRONICS AND COMMUNICATION ENGINEERING Submitted By: Under the
Supervision of HITESH MATHUR (9911102230) MR. AMIT SINGHAL ASHISH GOEL
(9911102194) AYUSH GUPTA (9911102229) DEPARTMENT OF ECE JAYPEE INSTITUTE OF
INFORMATION TECHNOLOGY, NOIDA (U.P) June , 2015 CERTIFICATE This is to affirm that
the work contained in this report titled as "CONTROLLING ROBOT WITH SPEECH
RECOGNITION" by Hitesh Mathur (9911102230), Ashish Goel (9911102194) and Ayush Gupta
(9911102199) in fractional satisfaction of the course work prerequisite of Bachelor of Technology in
Electronics and communication Engineering , Jaypee Institute of Information Technology, Noida is
a bonafide work did by them under my direction and supervision. The matter submitted in this report
has not been conceded for a recompense of whatever other degree anyplace unless unequivocally
referenced. Signed: Mr. Amit Singhal Project Supervisor ECE Department JIIT, Sec–128, Noida,
ABSTRACT In today 's reality, Robotics is a quickly developing and fascinating field. Robot has
adequate insight to cover the most extreme territory of gave space. We are showing a Speech
Control Robot For Robot control, which is controlled by utilizing discourse controller that is

Disadvantages Of FFT Implementation
FFT is very well developed in software but still a need to study on realizing it on hardware subsists.
Its primary advantage is the fact that the hardware implementation of FFT generally has more than
one computations running in parallel, while in the software implementation a single step is
processed at once. Therefore, a FFT hardware can have large amount of data running through the
circuit in comparison to those of sequential circuits as realized by software. 16–Point FFT
Implementation: A typical FFT processor has the following 3 modules 1 Address generator 2
Twiddle factor generator 3 Butterfly unit 4 Two memory banks – R0 and R1 The address generator
controls writing to and from the two memory banks and which memory bank is read. In addition to
this, it generates addresses for reading and writing the contents read from memory banks to the
Butterﬂy Unit. The address generator also ensures that no memory bank is read from and written to
concurrently. There are 3 read address and 3 write address buses. First data is read from one memory
bank, and after processing through the butterfly unit it is written to the other memory bank. ... Show
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We use a digital complex multiplier to carry out multiplication with the generated twiddle factors.
The complex adders then perform addition or substation of opposite arms. As the arm A has no
latency as compared to latency created by twiddle factor multiplier on arm B so a delay block is
needed on the block A so that the outputs on both the arms appear simultaneously. We have to take
into account that multiplying two 8 bit numbers produces 16 bit number. Also the multiplication of
signed integers sometimes produce redundant sign bits in the results. The result hence produced
won't be correct in magnitude. Therefore, bits are routed from the back ( 15 to 8 ) from the
multiplier to the adder, effectively performing a left–shift on the

Fourier Transform Infrared Spectroscopy ( Ftir )
In vitro dissolution studies Relative in vitro dissolution behaviour of pure docetaxel and optimized
SNEP was assessed in simulated gastric fluid without enzyme (500 mL; pH 1.2; 37±0.5°C) as
dissolution medium using USP type II paddle apparatus (Electrolab, India) at a paddle rotation speed
of 50 rpm. At predetermined time points, an aliquot of 5 mL was withdrawn and equal volume of the
fresh dissolution medium was replaced to maintain the medium volume constant. All the samples
were filtered using Millipore membrane filter (0.45 µm, Millipore, USA), diluted and the
concentration of docetaxel was assayed by HPLC. Various dissolution parameters such as
dissolution efficiency (DE), mean dissolution time (MDT), initial dissolution rate (IDR), and mean
dissolution rate (MDR) were calculated to assess the dissolution profiles [29,30]. Solid state
characterization Fourier transform infrared spectroscopy (FTIR) FTIR spectrum of the samples was
recorded by KBr disc method using Perkin Elmer FT–IR Spectrometer (Paragon 1000, PerkinElmer,
Waltham, Massachusetts, USA) to illustrate the promising interactions among components used in
the formulation. Powder sample (4 mg) and IR grade dry potassium bromide (KBr; 200 mg) were
mixed gently in a glass mortar, compacted to form the disk by applying a force of 5.5 metric tons
using a hydraulic press. The corresponding disks were scanned over the wave number range of
4000–400 cm–1 at a scanning speed of 4 scans /s with a resolution of 1 cm–1

Progressive Image Transmission Using Ofdm
PROGRESSIVE IMAGE TRANSMISSION USING OFDM Enrol. No. – 13102288 , 13102216
Name of Student – Aman Pandey, Naman Gogia Name of supervisor(s) – Dr. Abhinav Gupta
December – 2016 Submitted in partial fulfillment of the Degree of Bachelor of Technology
DEPARTMENT OF ELECTRONICS AND COMMUNICATION JAYPEE INSTITUTE OF
INFORMATION TECHNOLOGY, NOIDA TABLE OF CONTENTS Chapter No. Topics Page No.
Certificate from the Supervisor II Acknowledgement III Summary IV List of Figures V List of
Symbols and acronyms VI Chapter–1 Introduction Chapter–2 Background 2.1 – OFDM Basics 2.2 –
Overview of This OFDM Simulation Project Chapter 3 – Design and Implementation 3.1 –
Overview 3.2 – System Configurations and Parameters 3.3 – Input and Output Description and
Results B. Tech (Min 2 Chapters) Chapter 6 or more Conclusion Appendices A B C References
(IEEE Format) Publications of the Student 1 2 3 Brief Bio–data (Resume) of Student
CERTIFICATE This is to certify that the work titled "Progressive Image Transmission Using
OFDM" submitted by "Aman Pandey(13102288) and Naman Gogia(13102216)" in partial
fulfillment for the award of degree of Bachelor of Technology of Jaypee Institute of Information
Technology, Noida has been carried out under my supervision. This work has not been submitted
partially or wholly to any other University or Institute for the award of this or any other degree or
diploma. Signature of Supervisor ........................... Name of

Electronics and Communication Engineering (Ece) Syllabus...
2007–2008 JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY, HYDERABAD
B.TECH. ELECTRONICS AND COMMUNICATION ENGINEERING I YEAR COURSE
STRUCTURE Code Subject English Mathematics – I Mathematical Methods Applied Physics C
Programming and Data Structures Network Analysis Electronic Devices and Circuits Engineering
Drawing Computer Programming Lab. IT Workshop Electronic Devices and Circuits Lab English
Language Communication Skills Lab. Total T 2+1 3+1 3+1 2+1 3+1 2+1 3+1 25 P/D 3 3 3 3 3 15 C
4 6 6 4 6 4 6 4 4 4 4 4 56 JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY
HYDERABAD. B.TECH. ELECTRONICS AND COMMUNICATION ENGINEERING II Year
COURSE STRUCTURE Code Subject Mathematics – III Probability Theory and Stochastic
Processes Environmental Studies ... Show more content on Helpwriting.net ...
Hence, it is suggested that they read it on their own with topics selected for discussion in the class.
The time should be utilized for working out the exercises given after each section , as also for
supplementing the exercises with authentic materials of a similar kind for example, from newspaper
articles, advertisements, promotional material etc.. However, the stress in this syllabus is on skill
development and practice of language skills. 2. OBJECTIVES: a. To improve the language
proficiency of the students in English with emphasis on LSRW skills. b. To equip the students to
study academic subjects with greater facility through the theoretical and practical components of the
English syllabus. c. To develop the study skills and communication skills in formal and informal
situations. 3. SYLLABUS : Listening Skills: Objectives 1. To enable students to develop their
listening skill so that they may appreciate its role in the LSRW skills approach to language and
improve their pronunciation 2. To equip students with necessary training in listening so that can
comprehend the speech of people of different backgrounds and regions Students should be given
practice in listening to the sounds of the language to be able to recognise them, to distinguish
between them to mark stress and recognise and use the right intonation in sentences. Listening for
general content Listening to fill up information

Selection Of Excipients For Galantamine Hbr Orodispersible...
Selection of excipients for Galantamine HBr Orodispersible tablet through drug excipient
compatibility study
M.Jeevitha* and V.P.Pandey
Department of Pharmacy, Annamalai University, Annamalainagar, Chidambaram– 608002,
Tamilnadu, India
Email : jeevipharma@gmail.com
Abstract
Galantamine is a clinically useful drug in several neurological problems, including Alzheimer 's
disorder. The mechanism of Galantamine HBr is a tertiary alkaloid drug that has been advanced and
ordinary in some of countries in addition to the us and abundant countries in Europe as a treatment
for slight–to–mild Alzheimer 's disease (ad). Galantamine has a completely unique, twofold form of
action. it 's far a reversible, aggressive inhibitor of acetylcholinesterase (pain), and is the single drug
dynamically advertised for the control of advert with established pastime as an allosteric modulator
of nicotinic acetylcholine receptors (nAChRs). Preformulation will be initial stage inside the
reasonable formula of an active ingredient (API). For some system interactions studies are
especially essential. whilst there has been no interface a few of the selected drug– excipient or
excipient–excipient then the method might be a suitable one. the selection of suitable examine
technique to estimate the interaction most of the drug and the excipients is a pre formula examine
main maximum fulfillment. In modern–day period the thermal analytical strategies is useful to
examine the interaction have a stare at the

Nt1110 Research Paper
Coursework – part1 Name of student Abdalfettah Asharaa UoB number 14022053 File number 3
Test data a Number of signals 4 f v t Signal 1 72 1 0 Signal 2 281 9 2 Signal 3 456 6 3 491 10 1 Test
data b Number of signals 5 f v t cos or exp? Signal 1 44 7 3 cos Signal 2 299 4 5 cos Signal 3 338 14
6 cos Signal 4 55 10 – exp Signal 5 571 9 – exp Test data c i) Enter your numerical answers in the
boxes below f v t Signal 1 348 13 4 Signal 2 397 11 2.87 ≈ 3 Signal 3 491 3 5.84 ≈ 6 ii) The same
formula that used to analyse the value of "t" in the "test_data_b" is also used in the "test_data_c".
The formula is: Theta= tan–1 (imag/real) t= (Theta x 16)/ π. It is clear that the signal can be seen in
figure 1, is a non–stationary ... Show more content on Helpwriting.net ...
Students are asked to generate BER curves against SNR, and to add at least one of these to their
report, together with 100 to 200 words of description. Marks will be given for output curves that are
smooth and regular, and also for plots that show output over a wide range of SNR. After running the
file or the m–file given in simulation.zip "sim_multiple_hiperlan2a_1.m", got the curve that displays
BER "bit error rat" against SNR "signal to noise ratio". Using BER is to calculate the performance
of the transmitter, the receiver and the channel system. Figure 7 below represents the BER curve
against SNR and the received signal for the default value of SNR (1:10). It is clear that the curve is
not smooth and regular as result of the low value of the SNR and the error or the target number of
the error. Figure 7: The BER curve and the received signal for SNR value of 10. Also, The BER
curve can be improved by the target number of the error. It means that the value of that number can
be adjusted in Error Rate Calculation block in the "commhiperlan2a.mdl" in the simulation.zip
folder. In the previous RER curve in the figure 7, the value of the target number of error was 1000,

Measuring Heart Rate With A Smartphone
Measuring Heart Rate with a Smartphone By:Linteng Cai Zhe Cheng 1. ABSTRACT Smart phones
are becoming increasingly popular, its performance is improved fast, low–cost smart phone displays
as the physiological solution was measured with an accuracy and may be used beyond the potential
clinical environment. In this project, we use our fingers covering smartphone camera, filtering and
signal band –pass filter, and the detection signal to calculate the BPM ( beats per minute ) of the
peak. We also need to eliminate noise and smooth results by MATLAB code. 2. INTRODUCTION
Many people are beginning to use smart phones. This is because we can download it can ... Show
Finally, it will be a lower cost, if the application we use to measure heart rate. Our aim is to explain
how to measure the application by the camera HR. For some chronic diseases, you have to measure
the frequency of extremely HR . In real life, there are many conditions that may affect the heart
diseases and conditions which can be very complex. If the HR can not be on time monitoring, the
situation would be very, very bad. Measuring heart rate is the basic way to diagnosis of heart
disease. The doctor will use a stethoscope to listen to heart sounds. Sound off in the heart of the
heart valves cardiac cycle, from vibration, chordate tendineae, papillary muscle, ventricular wall
perspective, arterial blood flow in from the storm. Based on the heart sounds, myocardial
contractility, hemodynamic status , vascular resistance and pulmonary artery pressure can be
diagnosed. In the smart phone technology is very suitable for the measurement of the heart beat in a
smartphone. Such as camera, touch screen, CPU, WIFI and a few other things. The phone can help
patient to record their behavior may cause a number of diseases. We can use the phone as a sensor as
the physical information monitor records. It can also be recorded on the human body may affect the
other signal. Because the phone is easy to carry. Therefore, it can provide a convenient carried out
under different environmental measurements, such as home health checks, education environment,
operating rooms, emergency

Advantage And Disadvantage Of Multicarrier Transmission
3.1 Introduction Multicarrier transmission, also known as OFDM is a technique with a long history
back to 1960that has recently seen rising popularity in wireless and wire line. In the recent interest
in this technique is mainly due to the recent advances in digital signal processing technology. The
International standards making use of OFDM for high–speed wireless communications are already
established or being established by IEEE 802.11, IEEE, 802.16, IEEE 802.20 and ETSIBRAN
committees. For wireless applications, an OFDM–based system can be of interest because it
provides greater immunity to multipath fading, and impulse noise, in eliminates the need for
equalizers, efficient hardware implementation can be realized using FFT techniques. ... Show more
content on Helpwriting.net ...
The OFDM makes single–frequency networks possible, which is especially attractive for
broadcasting applications. 3.1.2 Disadvantages of OFDM Transmission: In the OFDM is more
sensitive to frequency offset and phase noise. In OFDM has a relatively large peak–to–average–
power ratio, which tends to reduce the power efficiency of the radio frequency (RF) amplifier. 3.1.3
Application of OFDM During the past decade, OFDM has been adopted in many wireless
communication standards networks, including European digital audio broadcasting system, and
terrestrial digital video broadcasting, and satellite terrestrial interactive multiservice infrastructure in
China. In addition, OFDM has been considered or approved by many groups are working in IEEE
standard, such as IEEE 802.11a/g/n standard network, IEEE 802.15.3a, and IEEE 802.16d/e. The
applications include wireless local area networks, wireless personal area networks and wireless
metropolitan networks. Currently, OFDMA is being investigated as one of the most promising radio
transmission techniques for LTE of the 3rd Generation Partnership Project (3GPP), International
Mobile Telecommunications–Advanced

Different Methods For Harmonic Distortion
INTRODUCTION
Different detection methods for harmonic distortion already exist, but the following shortage make
them did not reflect fully the influence of harmonic on distribution system [4]: Don't consider the
progressive effect of harmonic current on the energy dissipation in distribution system. Don't
distinguish the direction of harmonic distortion. Does the customer with nonlinear Loads pollutes
the distribution system or the utility background harmonic pollutes the customer with linear loads?
Harmonics represents a financial lamb to customers who do not generate them, so the harmonic
distortion penalty should be inclusive in a utility's rate structure.
In the present, the tariff of the electrical energy is based on the traditional concepts of active,
reactive, and apparent power, and related power factor. These concepts are well defined for
sinusoidal conditions. Unfortunately, in non sinusoidal conditions, these traditional definitions of
power component are not reliable anymore.
The paper concerns with this matter, and aims towards the development of an adequate method
dealing with the possibility of determining the responsibility of the harmonic distortion through
billing quantities . The authors have presented some research that established the idea of this paper,
as follows: The definitions of power components under non sinusoidal conditions in Ref. [2], which
include some parameters for the correct attribution of responsibility between customers and

Ftir History
History of the FTIR
The FTIR came from the IR (infrared) spectrum that was found in the 1800s. IR spectrum was
discovered by Sir William Herschel. A scientist named Peter Fellget had obtained the first IR
spectrum by using the FTIR in 1949.
The FTIR stands for Fourier Transfrom Infrared Spectroscopy. More FTIRs were being used by the
1960s. When matter and energy interact it produces wavelengths that can be seen by the FTIR.
Basically, all FT are waveforms that are just the sum of simply sinusoids of different frequencies. It
uses a mathematical tool that show how to deconstruct the waveform of the sinusoid components.
The FTIR analyzes the absorption of certain wavelengths by a solid or liquid sample. "FT–IR
Spectrometers are often ... Show more content on Helpwriting.net ...
It concluded that most of the components in the lamotrigine was Breyer's yeast. It also contained 4–
Bromopyridine HCL and 3,4–diamino–5–pyrazolol sulfate. However, based on research, it should
have yielded 3,5–diamino–6–(2,3–dichlorophenyl)–as–triazine as being a component in the
Lamotrigine. Lamotrigine's chemical name is 3,5–diamino–6–(2,3–dichlorophenyl)–as–triazine
(http://www.rxlist.com/lamictal–drug.htm). Each tablet contains the labeled amount of lamotrigine
and the following inactive ingredients: lactose; magnesium stearate; microcrystalline cellulose;
povidone; sodium starch glycolate; FD&C Yellow No. 6 Lake (100–mg tablet only)
(http://www.rxlist.com/lamictal–drug.htm).
The second type of medicine that I used in my experimentation was Hydrocodone. This medicine is
used to help deal with pain after surgery was performed. I had crushed the Hydrocodone tablet into
powdered form, so it can be placed on the handheld HazMatID FTIR sensor. Once it was in
powdered form, I had took the handheld HazMatID FTIR, selected the identify button, and then
sterilized the sensor on the FTIR with a alcohol pad. After sterilizing the sensor, I placed the powder
form of Hydrocodone onto the handheld HazMatID FTIR

Essay On Preprocessing Techniques
2.1 Preprocessing Module In this module, the input signals is prepossessed first, here Hamming
windowing technique is used and followed by the FFT [5]. Initially the input signal is spitted as
overlapping frames, and each frame contains the duration of 0.025ms. The block diagram of
preprocessing module is as shown in Fig1.
Preprocessing Module
Optimization Module
Spectral Filtering Module
Fig.1 Block diagram of speech signal enhancement
The input speech signal is denoted by S by having a total duration of T ms and the frames be
represented by Fi, where 1 ≤ i ≤ T/0.025 each having 0.025 ms. It can be represented by S = {F1
F2......... Fn}, when n=T/0.025 the frames are windowed by using the hamming window technique.
The hamming ... Show more content on Helpwriting.net ...
In PSO each member of the population is called particle, and each population is called a swarm.
PSO algorithm steps: Initially it generates a random population. In this case the initial population
consists of value interval [0, 1]. Compute the position and velocity of each and every particle.
Compute the best velocity for each particle and the best velocity for all particles in the iterations.
Update the new velocity, add it to the swarm particle and get the new particle.
Vt+1=vt+1/2αvt–1+1/6α(1–α)vt–2+1/24α(1–α)(– α)vt–3+Ψ_1 (ρ_b–ρ)+Ψ_2 (ω_b–ρ).....(3)
ρ_(t+1)=ρ_t+v_(t+1) .............. (4) After updating all the particles, evaluate using fitness function is
satisfied, the process ends otherwise the whole process is repeated from step3.
The fitness [1] in this paper depends on three terms. For calculating the fitness in this case, the
values are converted to zero or one. It can be represented by z, if z > 0.5 it is converted to 1,
otherwise 0. The initial noise power spectrum is denoted by Λ and noise spectrum variance is
denoted by spectrum distance can be calculated using equation 5.
〖SD〗^((t))=20 log_10⁡
〖ᴧ^t 〗– log‖W_j^((i)) ‖,where 0< m < M–1. After the windowing
technique followed by the Fast Fourier transforms (FFT) frequency domain signal is achieved. Let
the input windowed signals in the ith frame be represented as w_0^((i)),w_1^((i)),.......,w_(M–
1)^((i))and Fourier transform is given by: w_k^((i) )= ∑_(k=0)^(M–1)▒w_n^((i) ) e^(–i2πk

Speech Processing : Using Mel Frequency Cepstral...
Speaker reognition using Mel Frequency Cepstral Coefficients(MFCC)
Abstract Speech processing has emerged as one of the most important application area of digital
signal processing. Various fields for research in speech processing are speech recognition, speaker
recognition, speech analysis, speech synthesis, speech coding etc. The objective of automatic
speaker recognition is to extract, characterize the discriminant features and recognize the
information about speaker identity. In this paper we present a voice recognition system based on
Mel Frequency Cepstral Coefficients (MFCC) and vector Quantization (VQ). This technique has an
advantage that it creates fingerprint of human voice by exploiting human acoustic system and
cepstral analysis. MFCC is widely accepted as a baseline for voice recognition due to these unique
features.
KeywordsMFCC, Vector Quantization, Speaker recognition, Feature extraction, Fast Fourier
Transform
Introduction
Human speech is the most natural form of communication and conveys both meaning and identity.
The identity of a speaker can be determined from the information contained in the speech signal
through speaker identiﬁcation. Speaker identiﬁcation is concerned with identifying unknown
speakers from a database of speaker models previously enrolled in the system. Speaker (voice)
identification has varied applications ranging from opening doors to security systems.
Speech processing is widely divided into 5 different

Advantages And Disadvantages Of Spectrum Sensing
Abstract The constrained available spectrum and the incompetence in the spectrum utilization and
administration require another correspondence innovation and communication technology..
Spectrum sensing is used to detect the (unlicensed) the unused (licensed) frequency bands. Spectrum
sensing includes locating the usage of spectrum and their features across different dimensions such
as code frequency ,time and space. The key features of CR system is that it senses the
electromagnetic environment to use their operation and dynamically vary its radio operating
parameters. With the likely transition of radio communications from static to dynamic spectrum
access in the near future, spectrum sensing has become an interesting area of research. Even though
many signal detection methods have a long history, economical implementations of consumer
devices employing spectrum sensing are still missing. In this research an overview of current state–
of–the–art spectrum sensing methods, limited to the binary decision of channel occupancy is
presented. Existing methods are categorized into energy detector, cyclostationary and matched filter
methods. A concise introduction and theoretical background of various spectrum sensing methods
based on their operation, and drawbacks. KEYWORDS Spectrum sensing, cooperative spectrum
sensing, MIMO, Cognitive radio Dynamic Spectrum Access (DSA), Primary User (PU), Secondary
User (SU), Software Defined Radio (SDR) 1. INTRODUCTION In the context of wireless
communications, spectrum sensing ... Show more content on Helpwriting.net ...
1 in the below diagram it shows the principle of spectrum sensing. the PU transmitter is sending data
to the PU receiver in a licensed spectrum band while a pair of SUs intends to access the spectrum.
To protect the PU transmission, the SU transmitter needs to perform spectrum sensing to detect
whether there is a PU receiver in the coverage of the SU

Essay On How To Solve The Sparse Approximate Dft Problem
The first work that tried to solve the sparse approximate DFT problem can be found in
cite{NYN93}, in which they designed an algorithm based on Hadamard Transform, i.e. the Fourier
transform over the Boolean cube. A polynomial time algorithm to interpolates a sparse polynomial
was developed in cite{Y95}. The method in this paper inspired the authors of cite{GMS05}, in
which they described an algorithm that can be used to approximate DFT when $N$ is a power of 2.
In the early 2000s, people paid a lot of attention to the sparse approximation problem in Fourier
space. The first algorithm with sub–linear runtime and the sub–sampling property was given in
cite{GGIMM02}. In which they give a randomized algorithm with runtime poly($s, log N, ...
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However, it needs to point out that the runtime of the algorithm in cite{AGS03} has a high
dependence on sparsity compare with cite{GGIMM02} and cite{GMS05}.
All the SFT algorithms above are randomized algorithms. This means they have small probability to
fail to give the correct or optimal recovery on each input signal. Thus, they are not appropriate for
long–lived failure intolerant applications. The first deterministic sub–linear time SFT algorithm was
developed in cite{I08} based on the deterministic Compressed Sensing results of Cormode and
Muthukrishnan (CM)cite{RSR69}cite{CM05}cite{CM06}. A simpler optimized version of this
algorithm was given in cite{I10}, which has similar runtime/sampling bounds ($mathcal{O}(s^2
log ^4 N)$) to the one in cite{GMS05}. Later, in cite{I11}, a further modified SFT algorithm was
provided. It showed simple methods for extending the improved sparse Fourier transforms to higher
dimensional settings. More specifically, the algorithm can find the near optimal $s$–term
approximation for any given input function, $f: [0,2pi]^{D} rightarrow C$ in $mathcal{O}(s^2
D^4)$ time (neglecting logarithmic factors). The algorithms in cite{I08}cite{I10}cite{I11} are all
aliasing–based search algorithm cite{indyk_overview}, which means they rely on the combinatorial
properties of aliasing among frequencies in sub–samples DFTs. The algorithms

Glycerol: Fourier Transform Infrared Spectrometry
Treated glycerol and commercial glycerol were analyzed using the Fourier Transform Infrared
Spectrometry (FTIR) to determine the functional group. The functional group is a group of atoms
that replace the hydrogen in the organic compound. The structure of organic family compounds and
their properties are defined by organic compounds. Table 4.3 shows the comparison data for the
glycerol residue, recovered glycerol and commercial glycerol. Table 4.3: Comparing the functional
group for treated glycerol and commercial glycerol Functional Group Spectra Value (cm –1) Treated
glycerol Commercial glycerol Hydroxyl (O–H)– 3394.2700 3299.9600 Aromatic methoxyl (C–H)
2950 2934.1100 Alkenes (C=C) N/A 3022 Soap (COO) 1365.4100 1455 Carbonyl (–C=O)
1645.6200 NAAlcohol (C–OH) 1015.2800 1038.5400 ... Show more content on Helpwriting.net ...
The hydroxyl group which is O–H appeared at a spectra value of 3394.2700 cm–1for the treated
glycerol and 3299.9600 cm–1 for the commercial group. This common hydroxyl group has water in
its contents and also has a percentage of water (Yong et al., 2001). The presence of soap (COO
functionality) was indicated by the absorption frequency of 1565.4100 cm–1 which was present in
treated glycerol and 1455 cm–1 in commercial glycerol. Groups that contained oxygen were
carbonyl (C=O) and alcohol (C–OH) with each bonding present for a different activity based on the
location and also with a hybridization of C–O bond. The presence of carbonyl (C=O) did appear in
treated glycerol at 1645.6200 cm–1 but not in commercial glycerol. This is caused by some
impurities during product oxidation of glycerol for example glyceraldehydes, dihydroxyacetone and
also free fatty acids (Yong et al., 2001). The alcohol group (C–OH) also appears in treated and
commercial glycerol at a spectra value of 1015.2800 cm–1 and 1038.5400

Varied Potentials of Aspergillus Species in Synthesis of...
Conclusions
To conclude, though use of Aspergillus species is common in synthesis of metal nanoparticles, these
five species are not well studied. Among them, A. fischeri confirms a good quality production of
AgNPs at an incredibly low concentration of salt solution used but with more number of bigger
sized particles. However, efforts are underway to optimize the conditions in the process to obtain a
good size and shape morphology. Also, understanding the protein–nanoparticle interactions during
the synthesis mechanism shall guide us to the possibility of utilizing the present system as future
''nano–factories''. We aim to purify and characterize the proteins to comprehend their mode of action
and possible interactions with silver ... Show more content on Helpwriting.net ...
Characterization
Change in color was visually observed in the silver nitrate solution incubated with all five
Aspergillus species. The bio reduction of Ag+ in the aqueous solutions was screened by sampling of
aliquots at different time intervals. Absorption measurements were carried out on Thermo–scientific
UV–Visible Spectrophotometer from 200–800nm, at a resolution of 1 nm. A part of the dried
powdered sample was analysed by X–ray diffractometer as a preliminary confirmative method of
the presence of silver nanoparticles. The X–ray diffractometer (Rigaku Miniflex–11) was operated at
a voltage of 30 kV and a current of 15mA with CuKα radiation (λ=1.5406 Å) and at 2 theta angles,
intensities were recorded from 6°to 60°. To know the size of synthesized silver nanoparticles
(AgNPs), size distribution analysis was performed using dynamic light scattering in aqueous
solution. The hydrodynamic size of the silver nanoparticles was obtained using a Zeta–sizer
(Malvern) instrument applying a 660 nm laser. The software was optimized to report summary
statistics based upon the intensity of light scattered. Two milliliter sample volumes from each
nanosilver dispersion were loaded into glass cuvettes and summary statistics were obtained using
triplicate 2 minutes analyses (total analysis time=6minutes). For Fourier transform

The Coefficient Of Variation Of The Pixel Position
Where Itij is the images sampled discretely with the pixel position (i, j), gi,j is the spatial neigh–
borhood of the pixel(i, j), |gi,j| is the amount of pixels in the neighborhood window and Dt is the
size of time step. In Yu and Acton's [62] research, they had utilized the coefficient of variation of the
adaptive filtering technique to replace the gradient–driven diffusion coefficient c((rIt ij)p) and
named it the Instantaneous Coefficient of Variation or ICOV. Fig. 12. Illustration original images are
in the upper rows, Images processed by MAS– the reflection function–alities are in the lower rows
[62]. 2.3.5Difference of Gaussian (DoG) The technique known as the DoG filtering–based
normalization or DoG is a technique for nor–malization that depends on the variation of the
Gaussians filtering to create a normalized image [2, 38, 63]. Essentially, it uses a band–pass filtering
to the inputted image and after that creates a normalized version. It should be noted that prior to
utilizing the filter, one has use the gamma correction or the log transformation on the image;
otherwise the outcome will not be as antici–pated [64]. The model of illumination–reflectance can
be utilized to design a frequency–domain method in enhancing the image's appearance using the
gray–level ranged compression and simultaneously contrasting the enhancements [54,65]. This
model suggests that each pixel value f(x, y) can be reflected as the outcome of an illumination
component i (x, y) and a

Chase-Pyndiah Et. Al. : How Do You Could Be Used?
SOVA–based decoding is generally inferior to the MAP–based decoding in terms of BER
performance. The authors show that the original SOVA introduces two types of distortions in its
output. They show that the performance of the SOVA can be improved by normalizing its output and
eliminating the correlation between intrinsic and the extrinsic information derived in each decoding
iteration. A modified updating rule can also be applied to improve performance. It was discovered
that the original SOVA proposed in [48] omits some updates for ease of implementation, leading to
overestimation of the reliability [51]. It was proved that the modified SOVA of [48] is equivalent to
Max–log–MAP algorithm [52]. Application of SOVA–based SISO decoding for ... Show more
either +1 or –1; where +1 represents a bit 1 and –1 represents a bit 0); and it is possible that one or
both of c+ and c– may not exist due to the fact that the Chase algorithm operates using a subset of
the 2n possible codewords. In the event that there are not two competing codewords, the Pyndiah
algorithm uses a scaling factor, βm, which approximates the value of the extrinsic information for
the mth decoding. These values, which are a function of m, are specified in [47]. The values for βm
in [44] are approximated using computer simulation of a (64,57)2 BTC (the superscript "x" indicates
x dimensional BTC). A simple, yet effective alternative for approximating βm, which does not
require computer simulation, is presented in [53]. A soft–input value, λi,j, is computed by the
decoder for each entry in C. These soft–values are used to select the codewords in each subset, the
competing codewords, as well as, in computing the extrinsic information. The soft–input is
computed using: (10) where αm is a scaling factor, which is either pre–defined for increasing values
of m [44], or computed after every decoding by assuming that the extrinsic information is governed
by Gaussian statistics [53]; a method that is very similar to the one used in computing the scaling
factor in [50]. The above equations demonstrate how to compute the soft–input and extrinsic
likelihood values for a row decoder. For the

What Is A Four-Distributed Static Compensator
This paper deals with a four–leg distributed static compensator (DSTATCOM) which is used to
solve the current related power quality. An amplitude adaptive notch filter (AANF) is employed for
the reference current extraction of DSTATCOM control scheme because of its simplicity, capability
of frequency and amplitude measuring, appropriate extraction of the fundamental signal, and
insensitivity to the amplitude variation of the input signal. To generate the gate pulses of the
switches, an adaptive hysteresis band current controller is used. In addition, fuzzy logic controllers
are used for a better performance of DSTATCOM under dynamic conditions. The proposed control
algorithm is robust to power disturbances, especially when the main voltage ... Show more content
on Helpwriting.net ...
However, these algorithms generally demonstrate a slow time response. Time–domain algorithms
are based on the instantaneous extraction of harmonic currents/voltages. The common time–domain
control strategies are instantaneous reactive power theory (IRPT) [6] and synchronous reference
frame theory (SRF) [7]. Calculation of active and reactive powers by transforming three–phase
voltages and currents into two phases is the principle of PQ theory, which does not work properly
under non–sinusoidal supply conditions [8]. SRF theory is based on conversion of three–phase
quantities into their corresponding dc components, and low–pass filters (LPFs) are employed for
harmonic filtering which contain a time delay and deteriorate the performance of the controller [9].
Most of the advanced control and signal processing methods are accurate and show a better dynamic
response than the FFT, but a large amount of calculations is required, which does not demonstrate an
excellent performance in frequency–varying conditions [10–13]. Adaptive notch filter (ANF) is
another advanced algorithm which has been introduced as an effective control technique for
extracting reference sinusoidal components from distorted input signal. ANF is capable of changing
the notch frequency suitably by tracking the frequency variations of the input signal [14–16].
To the best knowledge of the authors, the modified notch filter in a

Advantages And Disadvantages Of Multicarrier Modulation
Multicarrier modulation is a technique of transmitting data over several subchannels instead of
transmitting the data over the whole bandwidth in single carrier systems. The data stream to be
transmitted is divided into a number of lower data rate data streams. The subchannels have narrow
bandwidth compared to wideband channel in single carrier systems and also the symbol period on
each subchannel is increased.
Multicarrier modulation provides immunity to fading caused by data transmission over mul–tipath
fading channels or frequency– selective fading channels. Each of the subchannel expe–riences flat
fading due to the decreased bandwidth. Also, due to the increase in the symbol period, it provides
enhanced immunity to ISI. Another advantage of multicarrier modulation technique is it can provide
better spectral efficiency compared to single carrier modulation, since the spectrum of the subcarrier
can be overlapped.
Although there are advantages, multicarrier modulation technique has disadvantages such as
requirement of synchronization with marginal conditions , higher Peak–to–Average Power Ra–tio
(PAPR) implying strict requirement for amplifier to be linear.
A number of multicarrier modulation technique has involved. Few of them are OFDM, ... Show
These sub–carriers are orthogonal to each other. It is very much popular scheme used in digital
television, audio broadcasting and 4G communications. OFDM has the ability to deal with severe
channel fading conditions without complex equalization filters. Due to the longer symbol period and
the CP extension, OFDM is more robust against the effect of timing offset and delay spread in
multipath fading channels. OFDM also gain higher spectral efficiency due to the overlapping of the
subcarrier spectrum which are orthogonal to each other. The major drawback of OFDM is high

Biometric Codes Are Used For Recognising A User On The...
Abstract
Biometric systems are used for recognising a user on the basis of biometric traits he have. During
authentication some of the frequently asked questions are "Is he who he claims to be?", "Is he a
valid user for gaining access to the system?". Biometric system answers all these questions by
authenticating the users. Every second information is shared and transferred between people and it is
important to make sure that what is sent by sender is what received by the receiver thus raising the
demand of security. Steganography is one of the techniques used for securing the data. The secret
message is hidden inside a cover media like audio, video or image with the help of a secret key.
Biometric templates can also be secured with this technique. Instead of storing original templates in
the database stego–image is stored. LSB is one of the common techniques that replace the LSB of
every pixel of the cover image with the secret message to form stego–image.
Keywords: Biometric, Biometric Attacks, Biometric template, Steganography, Security.
1. Introduction
With increasing rate of attacks, everyone today needs a reliable and secure system. Biometric
systems fulfil the needs to a great extent as biometric traits are better than passwords or pins which
have chances of being stolen and forgotten. Before using biometric systems enrolment phase is
necessary during which the templates of the users are stored in the database. During authentication
user 's claim is matched with the

Obtaining Motion Blur Parameters Form The Frequency Spectrum
Obtaining Motion Blur Parameters Form The Frequency Spectrum
Fourier transform is applied on digital images to interprets their content in terms frequency
information. To illustrate, Flat areas, where the intensity is slowly changing, result in low
frequencies. Rough areas, on the other hand, result in high frequencies because of the dramatic
change in the intensity value. this paper discusses the impact of manipulating the frequency
information of digital images and how the frequency spectrum can be used to address a real world
situation.
Filtering an image in the frequency domain is usually composed of three steps. First, the Fourier
transform is calculated (DCT or DFT). Then, a certain operation is performed on the frequencies ...
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Huei and Kun [2] proposed that the speed of moving objects in a single image can be estimated
using the blur parameters, the camera parameters and imaging geometry. To illustrate, the
displacement of a moving object (d) can be determined using similar triangles according to the blur
length (k) Figure2. And by knowing the shutter speed of the camera (T), the speed of the object is v
=d/T(1). Since this paper is concerned with Fourier Transform, the details of equation (1) are
omitted and calculating the blur parameter is detailed below.
The blur parameters, including the blurs' direction and length, can be determined by examining their
impact on the Fourier spectrum. As shown in figure, the Fourier spectrum of the motion blur
contains strips of dark lines that are parallel and uniformly separated. Note that the Fourier spectrum
depends on the objects' orientation; so the direction of the motion blur could be extracted from the
frequency spectrum. Also, as the blurs' length increase, the edges get smoother, resulting in lower
frequency response. These observations suggest that the frequency spectrum has all the needed
information to determine the blurs parameters. In particular, the object shown in the figure is
moving along the horizontal axis, and this caused the vertical orientation of the dark lines in the
frequency spectrum. Furthermore, increasing the blurs length, which can be achieved by increasing
the object's speed, lessens the distance

Modern Transformers And Electric Power Systems
Large power modern transformers are vital components and very expensive in electric power
systems. Forthwith, it is very important to reduce the duration and frequency of unwanted outages
that results in a high demand imposed on power transformer protection relays, this includes the
requirements of dependability related with no mal–operations, operating speed related with short
fault clearing time to avoid extensive damage or to preserve power quality and power system
stability and security related with no false tripping.
Discrimination between inrush currents and internal faults has long been known as a challenging
power transformer protection problem. Otherwise, inrush currents contain large second harmonic
component compared to internal faults, conventional transformer protection are designed to achieve
required discrimination by sensing that large second harmonic content [1]. The level of second
harmonic component of the inrush current has been reduced due to improving in transformer core
material and occur power system changes. Additionally, a large second harmonic can also be found
in transformer internal fault currents if a shunt capacitor is connected to a transformer in a long extra
high voltage transmission line. Therefore, the methods based on the measurement of the second
harmonic are not sufficiently effective for differential protective relays [2].
Newly, several new protective schemes have been proposed to deal with the previous problem in
large power

Optical Resonance Imaging ( Mri )
Magnetic resonance imaging (MRI) is a technique that uses a magnetic field and radio waves to
create detailed images of the organs and tissues within your body. MRIs are largely used in the
medical field today because of their ability to create detailed images of the human body which can
be used for diagnostic purposes. In 1971 a paper in the journal Science Raymond Damadian, an
American physician and professor at the Downstate Medical Center State University of New York
reported that tumors and normal tissue can be distinguished by nuclear magnetic resonance (NMR).
He suggested that these differences could be used to diagnose cancer, though later research would
find that these differences, while real, aren't consistent enough for diagnostic purposes. Damadian 's
initial methods were flawed for practical use, relying on a point–by–point scan of the entire body
and using relaxation rates of the tissue in your body, which turned out not to be an effective
indicator of cancerous tissue.
During the 1970s a team led by John Mallard built the first functional full body MRI scanner at the
University of Aberdeen in Scotland. In August of 1980 they used this machine to obtain the first
clinical image of a patient 's internal tissue using Magnetic Resonance Imaging, which identified a
primary tumor in the patient 's chest, an abnormal liver, and a secondary cancer in his bones. This
machine was later used at St Bartholomew 's Hospital in London from 1983 to 1993. Mallard and
his team

Survey On Digital Image Watermarking Techniques
SURVEY ON DIGITAL IMAGE WATERMARKING TECHNIQUES
V.Belmer Gladson1Y.Sam Josuva2, Dr.R.Balasubramanian3
1Research Scholar, 2 Assistant Professor 3Professor,
Department of Computer Science&Engg, Manonmaniam Sundaranar University, Tamilnadu,
1vbgclassic1984@gmail.com 2sam.joejaki@gmail.com,3rbalus662002@yahoo.com
ABSTRACT– In recent years, digital media are widely popular, their security related issues are
becoming greater importance. Watermarking is the process of hiding digital data in a carrier signal.
Embedding a digital signal such as audio, video or image with the information which cannot be
removed easily is called digital watermarking. Digital watermarking mainly used to verify the
authenticity, integrity of the carrier signal or to show the identity of its owners. In this paper, we
present a survey on various digital watermarking techniques. This paper mainly concentrates a
detailed survey of all watermarking techniques on image watermarking types in today's world.
Index Terms – Digital watermarking, spatial domain, Least Significant Bit (LSB), Frequency
domain, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Discrete
Fourier Transform (DFT).
INTRODUCTION
The term digital watermarking was first emerged in 1993, Tirkel introduce two watermarking
techniques to hide the watermark data in the images [1].In recent years digital media are gaining
widely popular, and their security related issues are becoming greater importance. The protection
and

Analyzing Precise Electronic Structure Of The Different...
The core aim of the present work is to completely analyze precise electronic structure of the five
different doped BaTiO3 systems and the bonding interactions between the constituent atoms. This
aim is achieved successfully by adopting maximum entropy method (MEM). In this section, the
importance of electron density studies in structure analysis, the formalism of MEM method, the
principle, MEM methodology followed in this work to elucidate the electron density are given
elaborately.
1.9.2.1 Electron density The electron density is a quantum mechanical observable, that can be
measured through scattering experiments, in particular X–ray diffraction from the crystals. The
possibility of measuring charge density in a crystalline system from its X–ray diffraction pattern was
conceived several years ago when Debye and Scherrer explained the existence of halos in a powder
photograph where the images of the electronic orbit around the atoms [Debye et.al., 1918].
Electron density is the measure of probability of an electron being present at a specific location. The
regions of electron density are usually found around the atoms and its bonds. The probability of
locating an electron at one point (or) another can be calculated quantum mechanically. This
calculation gives a quantity called electron density. Electron can be viewed as a stationary wave (or)
a cloud of negative charges. The electron density is considered as a periodic function of position in a
crystal, reaches to a

Edge Detection And Frequency Domain
Edge Detection in Frequency Domain
A comparison between different Filtering techniques in Time and Frequncy Domain
Adithya R H
Department of Electronics and Communication
Sri Jayachamarajendra College of Engineering
Mysore, Karnataka, India rhadithya@gmail.com Akash Sharma
Department of Electronics and Communication
Sri Jayachamarajendra College of Engineering
Mysore, Karnataka, India akashshrm02@gmail.com Abstract–This paper presents a comprehensive
comparison of different high pass filtering techniques for Edge detection in both time domain and
frequency domain. The paper examines various kernels and compares the efficiency of the filtering
technique against the computation time for various sizes of images with various sizes of high–pass
filter kernels. We have made use of Sobel filter as the standard filter kernel against which other
techniques are compared.
Keywords–frequency domain; edge detection; sobel filter; laplacian; gaussian;
I. INTRODUCTION
Image sharpening and smoothening is perhaps one of the most ubiquitously used techniques in any
image processing application. While these are considered inexpensive operations, multiple use of
the same may become computationally intensive, and hence may make the overall application slow.
In this paper we examine and compare the performance of sharpening filters in time–domain and
frequency domain. While there are many apparent computational advantages in converting an image
into frequency domain to apply a

Essay On Fiber Communication System
There are certain inherent flaws with the optical transmission system like inter–symbol interference
and noise. This distortion is introduced by the narrow bandwidth and some distortions due to the
media through the optical signals travel. The linear transversal filter is used to reduce symbol
interference. The system designed to remove unknown distortion is called an adaptive equalizer. The
corrective measure is to identify the distortion and adjust accordingly with the objective to remove
it. The equalizer can be the supervised or unsupervised type. In the TV or radio Transmission, blind
equalizers are used. The literature survey of analysis of mean square error and space division
multiplexing technique and other system removing the ISI ... Show more content on Helpwriting.net
...
The equalizer converges to higher MSE. The noise PSD directed method iterated over 3000 km
transmission on all six modes and it tends to convergence at same MSE to get the standard –10 dB
normalized MSE (NMSE).The noise PSD directed algorithms require 47 blocks and the
conventional algorithm needs 48 blocks [6]. Sean O¨Arık et.al have proposed Long–haul mode–
division multiplexing (MDM) for adaptive multi–input–multi–output (MIMO) equalization to
reduce for modal crosstalk and modal dispersion. To minimize computational complexity, use
MIMO frequency–domain equalization (FDE).Polarization division multiplexing (PDM) system use
single mode fiber but its transmission effected by noise, fiber nonlinearity and dispersion. In multi–
mode fiber (MMF) with multi–input–multi–output (MIMO) transmission Increasing per–fiber
capacity can be achieved more readily by increasing spatial dimensionality the total number of
dimensions available for multiplexing, including spatial and polarization degrees of freedom
denoted by D. In first case two polarization modes of single mode fiber using D=2. This is made
possible by equalization techniques goes on going up with the upward drift of D and higher group
delay. In second case systems using modedivision multiplexing (MDM) in MMFs (D>2) receiver,
computational complexity increases because of an increase in D and because of the large group
delay (GD) spread

An Program Records The Voice
This program records the voice
'Get ready to record the voice '
%Read data of letter "a" sound
f1=wavread( 'vc_a ',22050);
%Transform the data using Fast Fourier Transform function
F1=fft(f1,11025);
%Compute to obtain the Normalized Power Spectrum Density of the
%transformed data
Pf1 = F1.* conj(F1)/11025;
Pf1 = transpose(Pf1); %Transpose
Pf1 = Pf1(1:2206); %Only the first 2206 sample data needed
f2=wavread( 'vc_a2 ',22050);
F2=fft(f2,11025);
Pf2 = F2.* conj(F2)/11025;
Pf2 = transpose(Pf2);
Pf2 = Pf2(1:2206);
f3=wavread( 'vc_a3 ',22050);
F3=fft(f3,11025);

Pf3 = F3.* conj(F3)/11025;
Pf3 = Pf3(1:2206);
%Compute the average of the three
Pf_AVG1 = (Pf1 + Pf2 + Pf3) / 3;
%Plot PSD of sound "a"
f = 100000*(0:2205)/22050; %Frequency range
mel = frq2mel(f);
figure(1);
plot(mel,Pf_AVG1);
title( 'The PSD of the Letter "a" Sound ');
xlabel( 'Frequency (Mel) ');
ylabel( 'Power ');
%–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
%Read data of letter "e" and "o" sounds also by neural networks
f4=wavread( 'vc_e ',22050);
F4=fft(f4,11025);
Pf4 = F4.* conj(F4)/11025;
Pf4 = Pf4(1:2206);
f5=wavread( 'vc_e2 ',22050);
F5=fft(f5,11025);
Pf5 = F5.* conj(F5)/11025;

Pf5 = Pf5(1:2206);
f6=wavread( 'vc_e3 ',22050);
F6=fft(f6,11025);
Pf6 = F6.* conj(F6)/11025;
Pf6 = Pf6(1:2206);
Pf_AVG2 = (Pf4 + Pf5 + Pf6) / 3;
figure(2);

Dsp Manual
www.jntuworld.com
Department of Electronics and Communication VCET,Hyderabad.
DIGITAL SIGNAL PROCESSING
LAB MANUAL
III YEAR II SEMESTER (ECE)
Prepared by: K. Ashok Kumar Reddy
Department of Electronics & Communications Engineering,
Visvesvaraya College of Engineering & Technology,
Ibrahimpatnam.
Digital Signal Processing Lab Manual
Page 1
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JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD III Year B.Tech.
ECE – II Sem L T/P/D C 0 –/3/2
DIGITAL SIGNAL PROCESSING LAB The programs shall be implemented in software (Using
MATLAB / Lab view / C programming/ Equivalent) and hardware (Using TI / Analog devices /
Motorola / Equivalent DSP ... Show more content on Helpwriting.net ...
Furthermore, it allows you to run such lists of commands such that you pass in data
Digital Signal Processing Lab Manual Page 4
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and/or get data back out (i.e. the list of commands is like a function in most programming
languages). Once you save a function, it becomes part of your toolbox (i.e. it now looks to you as if
it were part of the basic toolbox that you started with). For those with computer programming
backgrounds: Note that MATLAB runs as an interpretive language (like the old BASIC). That is, it
does not need to be compiled. It simply reads through each line of the function, executes it, and then
goes on to the next line. (In practice, a form of compilation occurs when you first run a function, so
that it can run faster the next time you run it.) MATLAB Windows : MATLAB works with through
three basic windows Command Window : This is the main window .it is characterized by MATLAB
command prompt >> when you launch the application program MATLAB puts you in this window
all commands including those for user–written programs ,are typed in this window at the MATLAB
prompt Graphics window: the output of all graphics commands typed in the command window are
flushed to the graphics or figure window, a separate gray window with white background color the
user can create as many windows as the system memory will allow Edit window: This is where you

Advantages And Disadvantages Of Fifir Spectrometers
5.2 FTIR INSTRUMENT:
Fourier Transform Infrared Spectrometer are widely used in food analysis ,petrochemical
engineering organic synthesis, polymer science, pharmaceutical industry . FTIR spectrometers can
be hyphenated to chromatography, and the detection of unstable substances the mechanism of
chemical reactions and can be investigated with such instruments.[27]
5.2.1 HISTORY:
The first one who found that a spectrum and its interferogram are related by a Fourier transform was
Lord Rayleigh, in 1892. But the Fellget was the first one who has converted an interferogram to its
spectrum. Fast Fourier transform method on which the modern FTIR spectrometer based was
introduced to the world by Turkey and Cooley in 1965. It has wide application ... Show more
One of the mirror is a stationary mirror and other one is a movable mirror. The beam splitter is used
to transmit half of the light and reflect half of the light. Subsequently, the transmitted light and the
reflected light strike the stationary mirror and the movable mirror. When reflected back by the
mirrors, two beams of light recombine with each other at the beam splitter.[27]
If the distances travelled by two beams are the same, it means that the distances between two
mirrors and the beam splitter are the same and the situation is defined as zero path difference (ZPD).
But imagine if the movable mirror moves away from the beam splitter, the light beam which strikes
the movable mirror will travel a longer distance than the light beam which strikes the stationary
mirror. The distance which the movable mirror is away from the ZPD is defined as the mirror
displacement and is represented by ∆. It is obvious that the extra distance travelled by the light
which strikes the movable mirror is 2∆. The extra distance is defined as the optical path difference
(OPD) and is represented by delta. Therefore, δ =

Essay On Adaptive Filters
Adaptive filters have been successfully applied to diverse fields including communications, speech
recognition, control systems, radar, seismology and biomedical engineering. Among various types of
adaptive algorithms, the least–mean–square (LMS) algorithm is well known and widely adopted due
to its simplicity and robustness to initial condition and noise. The performance of the LMS
algorithm, in terms of convergence rate, maladjustment, mean–square error (MSE), and
computational cost, is governed by the step– size. The frequency–domain (FD) adaptive filter
algorithm is known to be able to reduce the numerical complexity by using the overlap–and–save
implementation method. It incorporates block updating strategies where the fast Fourier ... Show
A variable step–size algorithm is proposed in,by focusing on achieving low residual error
specifically for the acoustic echo cancellation applications and also lacks of convergence analysis.
Thus, we are motivated to develop an FD step–size control for LMS algorithm. Our objective is to
achieve both fast convergence and low steady–state error, and to provide theoretical analysis on the
convergence. A new bin–wise block–varying step size for the FD LMS algorithm. The optimal
solution of step size at each iteration is derived by cancelling the a posteriori error in each frequency
bin, and its estimate is connected to the magnitude–squared coherence (MSC) function. This
Performs better than the existing FD algorithm in terms of both convergence rate and mean square
deviation (MSD). Furthermore, compared to the TD algorithm, the proposed method converges
faster in the presence highly of correlated filter input. 5.1.1 frequency–Domain Variable Step–Size
LMS The derivation of the proposed FD step size control algorithm,

What Is Fourier Transform
Accordingly, the magnitude of energy density produces the spectrum of function, which is
commonly indicated as color plots. To investigate the signal around time t of interest, window
function has chosen that is peaked around t. Therefore, the modified signal S_t (τ) is short and its
Fourier transform is called short–time Fourier transform (Satish 1998). The principle of STFT is to
divide the initial waveform signal into small segments with short–time window, apply Fourier
transform to each segment. However, due to the signal segmentation, this method has limitation in
time–frequency resolution. It can only be applied to analyze the segmented stationary signal or the
approximate stationary signal, but for the non–stationary signal, when ... Show more content on
Helpwriting.net ...
A continuous wavelet transform is expressed as: Where x(t)is the waveform signal, a is the scale
parameter, b is the time parameter and ψ(t)is the mother wavelet, which is a zero mean oscillatory
function centred around zero with a finite energy,∫_(–∞)^(+∞)▒〖ψ(t)dt=0〗, and "*" denotes
complex conjugate. By dilating via the scale parameter a and translations via the time parameter b,
wavelet transform of a waveform signal decomposes the signal to a number of oscillatory functions
with different frequencies and time (Jardine 2006). Similar as Fourier transform decomposes a
signal into a series of complex sinusoids, the wavelet transform decomposes a signal into a family of
wavelets. The difference is that sinusoids are smooth, symmetric, and regular but wavelets can be
ether symmetric or asymmetric, sharp or smooth, regular or irregular. The dilated and translated
versions of a prototype function are contained in the family of wavelets. The prototype function is
defined as a mother wavelet. The scale parameter a and time parameter b of wavelets formulate how
the mother wavelet dilates and translates along the time or space axis. Different types of wavelets
can be chosen for different forms of signals to best match the features of the signal. The flexibility
of selecting wavelets and the characteristic of wavelets make wavelet transform a beneficial tool for
obtaining reliable results and

Dc-Ac Essay
Pseudo DC link based multi–stage inverter topology is proposed in [26], shown in fig.6, in which
DC link is replaced with a pseudo–DC link shown in fig.3(b). As dc link is eliminated in this
topology leads to lesser cost, size and volume compared to previous topologies and almost same
reliability compared to the previous topology. However, this topology is suffering from poor power
decoupling and more harmonic content compared to previous topologies. Common remarks on DC–
AC–DC–AC Topologies: Topologies discussed from fig.4–6 have a high–frequency dc–ac inverter
at the input side, which converts input dc into high–frequency AC. This high–frequency AC voltage
level will be increased using HFT and then converted into dc by using a bridge ... Show more
This type of power conversion scheme generally preferred in most of the PV systems, called Two–
Stage Power Conversion Systems (TSPCS)[28–29]. To enhance the design flexibility and power
conversion ratio as well as energy harvesting capabilities, the dedicated dc–dc power converter must
be placed between PV module and inverter as shown in Fig.2. The main difference between dc–ac–
dc–ac and dc–dc–ac power conversion scheme is, the isolated converter is employed in the first
method whereas non–isolated dc–dc converter is employed in the second method. Boost, Buck–
Boost, SEPIC and Cuk converters are widely preferred for developing this TSPCSs. A simple
TSPCS based on dc–dc boost converter fed Half Bridge Inverter (HBI) and Full Bridge Inverter
(FBI) is shown in Fig.8 [28] and Fig.9 [29] respectively. They are treated as a conventional two–
stage solutions for solar PV applications. In the case of half–bridge topology, dc link is established
through the two equal capacitors. These two capacitors act as a three–terminal dc supply to the half–
bridge inverter, which converts dc to ac power. Which is then, processed through the filter before
feeding to load. In this case, only half of the boost converter voltage is converted into ac. However,
in the case of FBI based TSPCS, the full output voltage of boost converter is converted into ac. This
means that more output

Summary : ' Subcarrier Allocation ' Square
Figure 3.6 Waveforms of the QPSK mapping. 3.1.4 Subcarrier Allocation There are three reasons for
outlining the "Subcarrier Allocation" square. The principal is to apportion the information and pilot
subcarriers, the second is to embed invalid subcarriers which conveys "zero" data, and the third is to
execute the FFT shift. After this square, 64 inputs for IFFT are readied. The execution module is
portrayed in Figure 3.7. Two 64 x 16 double port irregular access recollections (RAMs) are utilized.
The invalid subcarriers are accomplished by characterizing the substance of the two RAMs at
relative locations to be zeros. Ports An of the RAMs are utilized for information transporter
composing, while ports B are committed for pilot composing and the 64–subcarrier perusing. They
are controlled by two counters. "Counter_We_48" square stores the 48 information transporter
positions. As per the locations indicated by it, the I and Q estimations of the information images are
built into two RAMs from ports A. In the meantime, FFT movement is inalienably performed.
"Counter_Rd_64" utilizes a counter to create the perusing locations of ports B. At the point when
ports B are empowered and "Counter_Rd_64" tallies from 0 to 63, the coveted 64 inputs for IFFT
are yielded and the "en_ifft" is high, telling the IFFT square to perform figuring. Figure 3.7
Implementation module of Subcarrier Allocation. The perusing ought to begin after the written work
is done. In this way, the yield of

Essay On Dynamic Range
Dynamic range defined as the range of the lightest and darkest areas of an image which camera can
successfully capture without losing detail. Our real–world environment dynamic range is high that
exceeds the capabilities of modern display devices with limited dynamic range. A problem appears
when displaying high dynamic range image in low dynamic range display devices, so the tone
mapping technique has been used to solve this problem. In this paper, new adjustment tone mapping
technique is presented for displaying high dynamic range image on a low dynamic range device
without any lose in image details and maintains contrast of the image. Instead of linearly scaling the
luminance of all pixels or introduce local gamma correction with ... Show more content on
Helpwriting.net ...
Tone mapping technique used to map high dynamic range images to low dynamic range image that
will be displayed on recent devices, thus keeping the image looking realistic. The tone mapping
operators can be classiﬁed into two categories: global operators and local operators. Global operator
task depends on the same mapping function is used for all the pixels of the input HDR image so,
global operators can be described as spatially uniform methods. Global tone mapping operators are
computationally very simple and maintain the intensity orders of the original scenes thus avoiding
''halo'' artifacts, but cause loss of details in the mapped images. Local operators which reproduce the
tonal values in a spatially variant manner because mapping function processes for each individual
pixel. Local operators characterized that more satisfying than global operators in terms of the detail
preservation and compression ratio of the dynamic range. Also, there are two tone mapping model
linear tone mapping model and nonlinear tone mapping model. Linear model does not need
multiscale decomposition or segmentation of the images into binary or fractional maps, where the
problems associated with layer decomposition are not found. Linear model not only interested in
making the output images looks natural by enhancing the pixel intensity more significantly in
highlights, but also satisfies high radiance similarity with

Essay On Medicinal Volume Information Recovery
incorporates three cases, specifically: added substance homomorphism; include homomorphism,
question picture highlight is not encoded; full homomorphism encryption strategy. In [15],
Bellafqira et al. proposed a protected usage of a substance based picture recovery (CBIR) technique
that works with homomorphic scrambled pictures from which it separates wavelet based picture
includes next utilized for ensuing picture examination. Test comes about show it accomplishes
recovery execution on a par with if pictures were prepared nonencrypted.
In this paper, we proposed a powerful calculation of encoded medicinal volume information
recovery in light of DWT (Discrete Wavelet Transform) and DFT (Discrete Fourier Transform).
Since DWT can't avoid ... Show more content on Helpwriting.net ...
B. 3D Discrete Fourier Transform (3D–DFT)Discrete Fourier Transform is an essential change in
the field of picture rocessing. Expecting that the span of the medicinal volume information is M * N
* P, at that point the three–dimensional Discrete Fourier Transform (3D–DFT) is characterized as
takes after:
M −1 N −1 P −1
F ( u , v , w )  ¦ f ( x , y , z ) ⋅e − j 2 π xu/M e − j 2 π yv/N e− j 2 π zw/P
x = 0 y = 0 z = 0 
u = 0,1, , M − 1; v = 0,1, , N − 1; w = 0,1, , P − 1;
The equation of Inverse Discrete Fourier Transform(3D–
IDFT) is as per the following:
1 M −1 N −1 P−1
f ( x, y, z) = ¦¦¦F (u, v, w) ⋅e j 2π xu/M e j 2π yv/N ej 2π zw/P
MNP u =0 v =0 w=0
x = 0,1, , M − 1; y = 0,1, , N − 1; z = 0,1, , P − 1;
Where f(x,y,z) is the testing an incentive in the spatial area, F(u,v,w) is the inspecting an incentive in

the recurrence space.
C. Calculated Map
Calculated guide is the most average and broadly utilized tumultuous framework, which is a one–
dimensional disorderly framework. Calculated Map is a nonlinear guide given by the accompanying
equation:
[ N + = μ [ N − [ N
Where 0 μ ≤ 4 is the branch parameter, xk ∈ 0,1 is
the framework variable,the emphasis numberis K.
At the point when μ ≤ , the framework will demonstrate a disorganized

A Review Of Adaptive Technique For Image Super Resolution

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