Download Free Digital Signal Processing Using Matlab Wavelets Added For Testing Purpose Book in PDF and EPUB Free Download. You can read online Digital Signal Processing Using Matlab Wavelets Added For Testing Purpose and write the review.

Although Digital Signal Processing (DSP) has long been considered an electrical engineering topic, recent developments have also generated significant interest from the computer science community. DSP applications in the consumer market, such as bioinformatics, the MP3 audio format, and MPEG-based cable/satellite television have fueled a desire to understand this technology outside of hardware circles. Designed for upper division engineering and computer science students as well as practicing engineers and scientists, Digital Signal Processing Using MATLAB & Wavelets, Second Edition emphasizes the practical applications of signal processing. Over 100 MATLAB examples and wavelet techniques provide the latest applications of DSP, including image processing, games, filters, transforms, networking, parallel processing, and sound. This Second Edition also provides the mathematical processes and techniques needed to ensure an understanding of DSP theory. Designed to be incremental in difficulty, the book will benefit readers who are unfamiliar with complex mathematical topics or those limited in programming experience. Beginning with an introduction to MATLAB programming, it moves through filters, sinusoids, sampling, the Fourier transform, the z-transform and other key topics. Two chapters are dedicated to the discussion of wavelets and their applications. A CD-ROM (platform independent) accompanies the book and contains source code, projects for each chapter, and the figures from the book.
This is the second volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This second book focuses on recent developments in response to the demands of new digital technologies. It is divided into two parts: the first part includes four chapters on the decomposition and recovery of signals, with special emphasis on images. In turn, the second part includes three chapters and addresses important data-based actions, such as adaptive filtering, experimental modeling, and classification.
This supplement to any standard DSP text is one of the first books to successfully integrate the use of MATLAB® in the study of DSP concepts. In this book, MATLAB® is used as a computing tool to explore traditional DSP topics, and solve problems to gain insight. This greatly expands the range and complexity of problems that students can effectively study in the course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, a fair amount of programming is required. Using interactive software such as MATLAB® makes it possible to place more emphasis on learning new and difficult concepts than on programming algorithms. Interesting practical examples are discussed and useful problems are explored. This updated second edition includes new homework problems and revises the scripts in the book, available functions, and m-files to MATLAB® V7.
This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and ÉcolePolytechnique in Paris. - Provides a broad perspective on the principles and applications of transient signal processing with wavelets - Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms - Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection, multifractal analysis, and time-varying frequency measurements - Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet - Content is accessible on several level of complexity, depending on the individual reader's needs New to the Second Edition - Optical flow calculation and video compression algorithms - Image models with bounded variation functions - Bayes and Minimax theories for signal estimation - 200 pages rewritten and most illustrations redrawn - More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics
"This book covers basic and the advanced approaches in the design and implementation of multirate filtering"--Provided by publisher.
Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the 'golden trio' in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. - Multiple color illustrations are integrated in the text - Includes an introduction to biomedical signals, noise characteristics, and recording techniques - Basics and background for more advanced topics can be found in extensive notes and appendices - A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670
This book uses MATLAB as a computing tool to explore traditional DSP topics and solve problems. This greatly expands the range and complexity of problems that students can effectively study in signal processing courses. A large number of worked examples, computer simulations and applications are provided, along with theoretical aspects that are essential in order to gain a good understanding of the main topics. Practicing engineers may also find it useful as an introductory text on the subject.
Chapter 1: Fourier Analysis................................................................................................................... 1 1.1 CTFS, CTFT, DTFT, AND DFS/DFT....................................................................................... 1 1.2 SAMPLING THEOREM.......................................................................................................... 16 1.3 FAST FOURIER TRANSFORM (FFT)................................................................................. 19 1.3.1 Decimation-in-Time (DIT) FFT..................................................................................... 19 1.3.2 Decimation-in-Frequency (DIF) FFT............................................................................ 22 1.3.3 Computation of IDFT Using FFT Algorithm................................................................ 23 1.4 INTERPRETATION OF DFT RESULTS............................................................................. 23 1.5 EFFECTS OF SIGNAL OPERATIONS ON DFT SPECTRUM....................................... 31 1.6 SHORT-TIME FOURIER TRANSFORM - STFT.............................................................. 32 Chapter 2: System Function, Impulse Response, and Frequency Response........................ 51 2.1 THE INPUT-OUTPUT RELATIONSHIP OF A DISCRETE-TIME LTI SYSTEM..... 52 2.1.1 Convolution...................................................................................................................... 52 2.1.2 System Function and Frequency Response................................................................... 54 2.1.3 Time Response................................................................................................................. 55 2.2 COMPUTATION OF LINEAR CONVOLUTION USING DFT...................................... 55 2.3 PHYSICAL MEANING OF SYSTEM FUNCTION AND FREQUENCY RESPONSE 58 Chapter 3: Correlation and Power Spectrum................................................................ 73 3.1 CORRELATION SEQUENCE................................................................................................ 73 3.1.1 Crosscorrelation............................................................................................................... 73 3.1.2 Autocorrelation.............................................................................................................. 76 3.1.3 Matched Filter................................................................................................................ 80 3.2 POWER SPECTRAL DENSITY (PSD)................................................................................. 83 3.2.1 Periodogram PSD Estimator........................................................................................... 84 3.2.2 Correlogram PSD Estimator......................................................................................... 85 3.2.3 Physical Meaning of Periodogram............................................................................... 85 3.3 POWER SPECTRUM, FREQUENCY RESPONSE, AND COHERENCE..................... 89 3.3.1 PSD and Frequency Response........................................................................................ 90 3.3.2 PSD and Coherence....................................................................................................... 91 3.4 COMPUTATION OF CORRELATION USING DFT ...................................................... 94 Chapter 4: Digital Filter Structure................................................................................ 99 4.1 INTRODUCTION...................................................................................................................... 99 4.2 DIRECT STRUCTURE ........................................................................................................ 101 4.2.1 Cascade Form................................................................................................................ 102 4.2.2 Parallel Form............................................................................................................... 102 4.3 LATTICE STRUCTURE ..................................................................................................... 104 4.3.1 Recursive Lattice Form................................................................................................. 106 4.3.2 Nonrecursive Lattice Form........................................................................................... 112 4.4 LINEAR-PHASE FIR STRUCTURE ................................................................................ 114 4.4.1 FIR Filter with Symmetric Coefficients...................................................................... 115 4.4.2 FIR Filter with Anti-Symmetric Coefficients........................................................... 115 4.5 FREQUENCY-SAMPLING (FRS) STRUCTURE .......................................................... 118 4.5.1 Recursive FRS Form..................................................................................................... 118 4.5.2 Nonrecursive FRS Form............................................................................................. 124 4.6 FILTER STRUCTURES IN MATLAB ............................................................................. 126 4.7 SUMMARY ............................................................................................................................ 130 Chapter 5: Filter Design.............................................................................................. 137 5.1 ANALOG FILTER DESIGN................................................................................................. 137 5.2 DISCRETIZATION OF ANALOG FILTER.................................................................... 145 5.2.1 Impulse-Invariant Transformation............................................................................. 145 5.2.2 Step-Invariant Transformation - Z.O.H. (Zero-Order-Hold) Equivalent .............. 146 5.2.3 Bilinear Transformation (BLT).................................................................................. 147 5.3 DIGITAL FILTER DESIGN................................................................................................. 150 5.3.1 IIR Filter Design............................................................................................................ 151 5.3.2 FIR Filter Design......................................................................................................... 160 5.4 FDATOOL................................................................................................................................ 171 5.4.1 Importing/Exporting a Filter Design Object................................................................ 172 5.4.2 Filter Structure Conversion........................................................................................ 174 5.5 FINITE WORDLENGTH EFFECT..................................................................................... 180 5.5.1 Quantization Error......................................................................................................... 180 5.5.2 Coefficient Quantization............................................................................................. 182 5.5.3 Limit Cycle.................................................................................................................. 185 5.6 FILTER DESIGN TOOLBOX ............................................................................................ 193 Chapter 6: Spectral Estimation................................................................................... 205 6.1 CLASSICAL SPECTRAL ESTIMATION.......................................................................... 205 6.1.1 Correlogram PSD Estimator......................................................................................... 205 6.1.2 Periodogram PSD Estimator....................................................................................... 206 6.2 MODERN SPECTRAL ESTIMATION ............................................................................ 208 6.2.1 FIR Wiener Filter........................................................................................................ 208 6.2.2 Prediction Error and White Noise.............................................................................. 212 6.2.3 Levinson Algorithm.................................................................................................... 214 6.2.4 Burg Algorithm........................................................................................................... 217 6.2.5 Various Modern Spectral Estimation Methods......................................................... 219 6.3 SPTOOL .................................................................................................................................. 224 Chapter 7: DoA Estimation......................................................................................... 241 7.1 BEAMFORMING AND NULL STEERING...................................................................... 244 7.1.1 Beamforming................................................................................................................. 244 7.1.2 Null Steering................................................................................................................ 248 7.2 CONVENTIONAL METHODS FOR DOA ESTIATION................................................ 250 7.2.1 Delay-and-Sum (or Fourier) Method - Classical Beamformer.................................. 250 7.2.2 Capon's Minimum Variance Method......................................................................... 252 7.3 SUBSPACE METHODS FOR DOA ESTIATION............................................................ 253 7.3.1 MUSIC (MUltiple SIgnal Classification) Algorithm................................................. 253 7.3.2 Root-MUSIC Algorithm............................................................................................. 254 7.3.3 ESPRIT Algorithm...................................................................................................... 256 7.4 SPATIAL SMOOTHING TECHNIQUES ........................................................................ 258 Chapter 8: Kalman Filter and Wiener Filter............................................................. 267 8.1 DISCRETE-TIME KALMAN FILTER.............................................................................. 267 8.1.1 Conditional Expectation/Covariance of Jointly Gaussian Random Vectors............. 267 8.1.2 Stochastic Statistic Observer...................................................................................... 270 8.1.3 Kalman Filter for Nonstandard Cases........................................................................ 276 8.1.4 Extended Kalman Filter (EKF).................................................................................. 286 8.1.5 Unscented Kalman Filter (UKF)................................................................................ 288 8.2 DISCRETE-TIME WIENER FILTER .............................................................................. 291 Chapter 9: Adaptive Filter.......................................................................................... 301 9.1 OPTIMAL FIR FILTER........................................................................................................ 301 9.1.1 Least Squares Method................................................................................................... 302 9.1.2 Least Mean Squares Method...................................................................................... 304 9.2 ADAPTIVE FILTER ............................................................................................................ 306 9.2.1 Gradient Search Approach - LMS Method.................................................................. 306 9.2.2 Modified Versions of LMS Method........................................................................... 310 9.3 MORE EXAMPLES OF ADAPTIVE FILTER ............................................................... 316 9.4 RECURSIVE LEAST-SQUARES ESTIMATION .......................................................... 320 Chapter 10: Multi-Rate Signal Processing and Wavelet Transform............................ 329 10.1 MULTIRATE FILTER........................................................................................................ 329 10.1.1 Decimation and Interpolation..................................................................................... 330 10.1.2 Sampling Rate Conversion....................................................................................... 334 10.1.3 Decimator/Interpolator Polyphase Filters................................................................ 335 10.1.4 Multistage Filters........................................................................................................ 339 10.1.5 Nyquist (M) Filters and Half-Band Filters.............................................................. 348 10.2 TWO-CHANNEL FILTER BANK ................................................................................... 351 10.2.1 Two-Channel SBC (SubBand Coding) Filter Bank.................................................. 351 10.2.2 Standard QMF (Quadrature Mirror Filter) Bank.................................................... 352 10.2.3 PR (Perfect Reconstruction) Conditions.................................................................. 353 10.2.4 CQF (Conjugate Quadrature Filter) Bank................................................................. 354 10.3 M-CHANNEL FILTER BANK ......................................................................................... 358 10.3.1 Complex-Modulated Filter Bank (DFT Filter Bank)................................................ 359 10.3.2 Cosine-Modulated Filter Bank................................................................................. 363 10.3.3 Dyadic (Octave) Filter Bank.................................................................................... 366 10.4 WAVELET TRANSFORM ............................................................................................... 369 10.4.1 Generalized Signal Transform................................................................................... 369 10.4.2 Multi-Resolution Signal Analysis............................................................................ 371 10.4.3 Filter Bank and Wavelet........................................................................................... 374 10.4.4 Properties of Wavelets and Scaling Functions.......................................................... 378 10.4.5 Wavelet, Scaling Function, and DWT Filters......................................................... 379 10.4.6 Wavemenu Toolbox and Examples of DWT.......................................................... 382 Chapter 11: Two-Dimensional Filtering...................................................................... 401 11.1 DIGITAL IMAGE TRANSFORM..................................................................................... 401 11.1.1 2-D DFT (Discrete Fourier Transform)..................................................................... 401 11.1.2 2-D DCT (Discrete Cosine Transform)................................................................... 402 11.1.3 2-D DWT (Discrete Wavelet Transform)................................................................ 404 11.2 DIGITAL IMAGE FILTERING ....................................................................................... 411 11.2.1 2-D Filtering................................................................................................................ 411 11.2.2 2-D Correlation......................................................................................................... 412 11.2.3 2-D Wiener Filter...................................................................................................... 412 11.2.4 Smoothing Using LPF or Median Filter.................................................................... 413 11.2.5 Sharpening Using HPF or Gradient/Laplacian-Based Filter.................................. 414
This textbook is unique because of its in-depth treatment of the applications of wavelets and wavelet transforms to many areas, across many disciplines. The book is written to serve the needs of a one or two semester course at either the undergraduate or graduate level. The author uses a very simplified, accessible approach that de-emphasizes mathematical rigor. The presentation includes many diagrams to illustrate points being discussed and uses MATLAB for all of application code. The author reinforces concepts introduced in the book with easy to grasp review questions and problems, tailored to each specific chapter for better mastery of the subject matter. This book enables students to understand the fundamental concepts of wavelets and wavelet transforms, as well as how to use them for problem solutions in digital signal and image processing, mixed-signal testing, space applications, aerospace applications, biomedical, cyber security, homeland security and many other application areas.