Adaptive Filter Theory by Simon Haykin

Introduction:
Adaptive Filter Theory looks at both the mathematical theory behind various linear adaptive filters with finite-duration impulse response (FIR) and the elements of supervised neural networks. Up-to-date and in-depth treatment of adaptive filters develops concepts in a unified and accessible manner. This highly successful book provides comprehensive coverage of adaptive filters in a highly readable and understandable fashion. Includes an extensive use of illustrative examples; and MATLAB experiments, which illustrate the practical realities and intricacies of adaptive filters, the codes for which can be downloaded from the Web. Covers a wide range of topics including Stochastic Processes, Wiener Filters, and Kalman Filters. For those interested in learning about adaptive filters and the theories behind them.

Contents:
1. Stochastic Processes and Models.
 2. Wiener Filters.
 3. Linear Prediction.
 4. Method of Steepest Descent.
 5. Least-Mean-Square Adaptive Filters.
 6. Normalized Least-Mean-Square Adaptive Filters.
 7. Transform-Domain and Sub-Band Adaptive Filters.
 8. Method of Least Squares.
 9. Recursive Least-Square Adaptive Filters.
10. Kalman Filters as the Unifying Bases for RLS Filters.
11. Square-Root Adaptive Filters.
12. Order-Recursive Adaptive Filters.
13. Finite-Precision Effects.
14. Tracking of Time-Varying Systems.
15. Adaptive Filters Using Infinite-Duration Impulse Response Structures.
16. Blind Deconvolution.
17. Back-Propagation Learning.

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Signal Processing First

Book Description
Designed and written by experienced and well-respected authors, this hands on, multi-media package provides a motivating introduction to fundamental concepts, specifically discrete-time systems. Unique features such as visual learning demonstrations, MATLAB laboratories and a bank of solved problems are just a few things that make this an essential learning tool for mastering fundamental concepts in today's electrical and computer engineering forum. Covers basic DSP concepts, integrated laboratory projects—related to music, sound and image processing. Other topics include new MATLAB functions for basic DSP operations, Sinusoids, Spectrum Representation, Sampling and Aliasing, FIR Filters, Frequency Response of FIR Filters, z-Transforms, IIR Filters, and Spectrum Analysis. Useful as a self-teaching tool for anyone eager to discover more about DSP applications, multi-media signals, and MATLAB.

Table of Contents
1. Introduction.
2. Sinusoids.
3. Spectrum Representation.
4. Sampling and Aliasing.
5. FIR Filters.
6. Frequency Response of FIR Filters.
7. z-Transforms.
8. IIR Filters.
9. Continuous-Time Signals and LTI Systems.
10. The Frequency Response.
11. Continuous-Time Fourier Transform.
12. Filtering, Modulation, and Sampling.
13. Computing the Spectrum.

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SOLUTION MANUAL
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
OTHER RESOURCES

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Signal Analysis: Wavelets, Filter Banks, Time-Frequency Transforms and Applications by Alfred Mertins

Book Description
Signal analysis gives an insight into the properties of signals and stochastic processes by methodology. Linear transforms are integral to the continuing growth of signal processes as they characterize and classify signals. In particular, those transforms that provide time-frequency signal analysis are attracting greater numbers of researchers and are becoming an area of considerable importance. The key characteristic of these transforms, along with a certain time-frequency localization called the wavelet transform and various types of multirate filter banks, is their high computational efficiency. It is this computational efficiently which accounts for their increased application. This book provides a complete overview and introduction to signal analysis. It presents classical and modern signal analysis methods in a sequential structure starting with the background to signal theory. Progressing through the book the author introduces more advanced topics in an easy to understand style. Including recent and emerging topics such as filter banks with perfect reconstruction, time frequency and wavelets. With great accuracy and technical merit, this book makes a useful and original contribution to the current literature.

Table of Contents
Signals and Signal Spaces.
Integral Signal Representations.
Discrete Signal Representations.
Examples of Discrete Transforms.
Transforms and Filters for Stochastic Processes.
Filter Banks.
Short-Time Fourier Analysis.
Wavelet Transform.
Non-Linear Time-Frequency Distributions.

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A Wavelet Tour of Signal Processing: The Sparse Way by S. Mallat - 3rd Ed.

Book Description
The new edition of this classic book gives all the major concepts, techniques and applications of sparse representation, reflecting the key role the subject plays in today's signal processing. The book clearly presents the standard representations with Fourier, wavelet and time-frequency transforms, and the construction of orthogonal bases with fast algorithms. The central concept of sparsity is explained and applied to signal compression, noise reduction, and inverse problems, while coverage is given to sparse representations in redundant dictionaries, super-resolution and compressive sensing applications.

Table of Contents
CHAPTER 1 - Sparse Representations
CHAPTER 2 - The Fourier Kingdom
CHAPTER 3 - Discrete Revolution
CHAPTER 4 - Time Meets Frequency
CHAPTER 5 - Frames
CHAPTER 6 - Wavelet Zoom
CHAPTER 7 - Wavelet Bases
CHAPTER 8 - Wavelet Packet and Local Cosine Bases
CHAPTER 9 - Approximations in Bases
CHAPTER 10 - Compression
CHAPTER 11 - Denoising
CHAPTER 12 - Sparsity in Redundant Dictionaries
CHAPTER 13 - Inverse Problems

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Digital Signal and Image Processing by Tamal Bose - Free PDF

Book Description
This book helps students develop a well-rounded understanding of these key areas by focusing on fundamental concepts, mathematical foundations, and advanced algorithms.the presentation is mathematically thorough with clear explanations, numerous examples, illustrations, and applications. In addition to problems, matlab-based computer projects are assigned at the end of each chapter, making this book ideal for laboratory-based courses. The text is appropriate for a stand-alone course on digital signal processing, or a course that introduces a combination of topics in signal processing and image processing. It contains sufficient background material for a fundamental course and ample advanced topics for graduate-level instruction.

Table of Contents
· chapter 1. Fundamental concepts.
· chapter 2. Fourier analysis.
· chapter 3. Z-transform and digital filters.
· chapter 4. Filter design and implementation.
· chapter 5. Multivariate signal processing.
· chapter 6. Finite-word length effects.
· chapter 7. Adaptive signal processing.
· chapter 8. Least-squares adaptive algorithms.
· chapter 9. Linear prediction.
· chapter 10. Image processing fundamentals.
· chapter 11. Image compression and coding.

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Introduction to Data Compression by Khalid Sayood - 3rd and 4th Eds.

Book Description
The need to efficiently store, manipulate, and transmit large masses of information is growing more rapidly than the capacity of systems to handle it. Engineers and computer scientists need a solid understanding of compression in order to work with the burgeoning variety of data types and increasingly data-intensive applications. This uniquely comprehensive book explains the fundamental theories and techniques of data compression, with the most complete coverage available of both lossy and lossless methods. Rather than simply describing current approaches, Sayood explains the theoretical underpinnings of the algorithms so that readers learn how to model structures in data and design compression packages of their own. Practitioners, researchers, and students will benefit from the balanced presentation of theoretical material and implementations.

Table of Contents
Introduction
Mathematical Preliminaries for Lossless Compression
Huffman Coding
Arithmetic Coding
Dictionary Techniques
Context-Based Compression
Lossless Image Compression
Mathematical Preliminaries for Lossy Coding
Scalar Quantization
Vector Quantization
Differential Encoding
Mathematical Preliminaries for Transforms, Subbands, and Wavelets
Transform Coding
Subband Coding
Wavelets
Wavelet-Based Image Compression
Audio Coding
Analysis/Synthesis and Analysis by Synthesis Schemes
Video Compression

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Signals and Systems using MATLAB by Luis Chaparro 1st and 2nd Eds.

Book Description
This new textbook in signals and systems provides a pedagogically rich approach to what can commonly be a mathematically dry subject. With features like historical notes, highlighted common mistakes, and applications in controls, communications, and signal processing, Chaparro helps students appreciate the usefulness of the techniques described in the book. Each chapter contains a section with MatLab applications.• Pedagogically rich introduction to signals and systems using historical notes, pointing out "common mistakes", and relating concepts to realistic examples throughout to motivate learning the material

Table of Contents

Part 1: Introduction
Chapter 0 - From the Ground Up!
Part 2: Theory and Application of Continuous-Time Signals and Systems
Chapter 1 - Continuous-time Signals
Chapter 2 - Continuous-time Systems
Chapter 3 - The Laplace Transform
Chapter 4 - Frequency Analysis: The Fourier Series
Chapter 5 - Frequency Analysis: The Fourier Transform
Chapter 6 - Application of Laplace Analysis to Control
Chapter 7 - Fourier Analysis in Communications and Filtering
Part 3: Theory and Application of Discrete-Time Signals and Systems
Chapter 8 - Sampling Theory
Chapter 9 - Discrete-time Signals and Systems
Chapter 10 - The Z-transform
Chapter 11 - Fourier Analysis of Discrete-time Signals and Systems
Chapter 12 - Introduction to the Design of Discrete Filters

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Signals and Systems Laboratory with MATLAB by Alex Palamides

Book Description
With its exhaustive coverage of relevant theory, Signals and Systems Laboratory with MATLAB® is a powerful resource that provides simple, detailed instructions on how to apply computer methods to signals and systems analysis. Written for laboratory work in a course on signals and systems, this book presents a corresponding MATLAB implementation for each theoretical concept introduced, making it a powerful learning tool for engineers, scientists, and students alike.

MATLAB code is used in problems and examples presented throughout the book. This code and other learning materials are available in a downloadable supplement.

Due to the extensive—and truly unique—integration of MATLAB throughout this book, the authors provide a complete tutorial on use of the language for signals and systems analysis. With more than 5,000 lines of MATLAB code and more than 700 figures embedded in the text, the material teaches readers how to program in MATLAB and study signals and systems concepts at the same time, giving them the tools to harness the power of computers to quickly assess problems and then visualize their solutions.

Among its many useful features, this book:

Offers complete coverage of the signals and systems theory, starting with elementary signals and concluding with state-space modeling
Contains more than 400 examples and chapter-end solved problems
Executes commands one-by-one at the MATLAB command prompt, and results, along with comments, encouraging students to learn MATLAB on the fly

Additional Pedagogical Features:

A detailed MATLAB tutorial to introduce a beginner programmer to the language
Laboratory exercises that give students hands-on experience and help professors organize a course laboratory component
Presentation of continuous- and discrete-time in parallel fashion, effectively illustrating the similarities and differences between the two
Step-by-step examples that present data in tabular format and usually offer several different solutions to each problem

Table of Contents
Introduction to MATLAB
Signals
Systems
Time Domain System Analysis
Fourier Series
Fourier Transform
Fourier Analysis of Discrete-Time Systems
Frequency Response
Laplace Transform
z-Transform
Transfer Function

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Continuous and Discrete Time Signals and Systems by Mrinal Mandal & Amir Asif

Book Description
This textbook presents an introduction to the fundamental concepts of continuous-time (CT) and discrete-time (DT) signals and systems, treating them separately in a pedagogical and self-contained manner. Emphasis is on the basic signal processing principles, with underlying concepts illustrated using practical examples from signal processing, multimedia communications, and bioinformatics. Following introductory chapters, the text is separated into two parts. Part I covers the theories, techniques, and applications of CT signals and systems and Part II discusses these topics for DT, so that the two can be taught independently or together. Accompanying the book is a CD-ROM containing MATLAB code, audio clips, images, interactive programs, and signal animations. With over 300 illustrations, 285 worked examples and 385 homework problems, this textbook is an ideal introduction to the subject for undergraduates in electrical and computer engineering. Further resources, including solutions for instructors, are available online at www.cambridge.org/9780521854559.

Table of Contents
1. Introduction to signals
2. Introduction to systems
Part I. Continuous Time Signals and Systems:
3. Time domain analysis of systems
4. Signal representation using Fourier series
5. Continuous-time Fourier transform
6. Laplace transform
7. Continuous-time filters
8. Case studies for CT systems
Part II. Discrete Time Signals and Systems:
9. Sampling and quantization
10. Time domain analysis
11. Discrete-time Fourier series and transform
12. Discrete Fourier transform
13. Z-transform
14. Digital filters
15. FIR filter design
16. IIR filter design
17. Applications of digital signal processing

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Probabilistic Methods of Signal and System Analysis (3rd Ed.) - Free PDF Download

Book Description
Probabilistic Methods of Signal and System Analysis, 3/e stresses the engineering applications of probability theory, presenting the material at a level and in a manner ideally suited to engineering students at the junior or senior level. It is also useful as a review for graduate students and practicing engineers. Thoroughly revised and updated, this third edition incorporates increased use of the computer in both text examples and selected problems. It utilizes MATLAB as a computational tool and includes new sections relating to Bernoulli trials, correlation of data sets, smoothing of data, computer computation of correlation functions and spectral densities, and computer simulation of systems. All computer examples can be run using the Student Version of MATLAB. Almost all of the examples and many of the problems have been modified or changed entirely, and a number of new problems have been added. A separate appendix discusses and illustrates the application of computers to signal and system analysis.

Table of Contents
1. Introduction to Probability
2. Random Variables
3. Several Random Variables
4. Elements of Statistics
5. Random Processes
6. Correlation Functions
7. Spectral Density
8. Response of Linear Systems to Random Inputs
9. Optimum Linear Systems

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Encyclopedia of Electronic Components Volume 2: LEDs, LCDs, Audio, Thyristors, Digital Logic, and Amplification

Book Description
This book is perfect for teachers, hobbyists, engineers, and students of all ages, this reference puts reliable, fact-checked information right at your fingertips--whether you're refreshing your memory or exploring a component for the first time. Beginners will quickly grasp important concepts, and more experienced users will find the specific details their projects require.

Table of Contents
1. SCR
2. diac
3. triac
4. solid-state relay
5. optocoupler
6. comparator
7. op-amp
8. digital potentiometer
9. timer
10. logic gate
11. flip-flop
12. shift register
13. counter
14. encoder
15. decoder
16. multiplexer
17. LCD
18. incandescent lamp
19. neon bulb
20. fluorescent light
21. laser
22. LED indicator
23. LED area lighting
24. LED display
25. vacuum-fluorescent display
26. electroluminescence
27. transducer
28. audio indicator
29. headphone
30. speaker

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Signal and Image Processing for Biometrics by Amine Nait-Ali

Book Description
The aim of this book is to deal with biometrics in terms of signal and image processing methods and algorithms. This will help engineers and students working in digital signal and image processing deal with the implementation of such specific algorithms. It discusses numerous signal and image processing techniques that are very often used in biometric applications. In particular, algorithms related to hand feature extraction, speech recognition, 2D/3D face biometrics, video surveillance and other interesting approaches are presented. Moreover, in some chapters, Matlab codes are provided so that readers can easily reproduce some basic simulation results.

Table of Contents
1. Introduction to Biometrics
2. Introduction to 2D Face Recognition
3. Facial Soft Biometrics for Person Recognition
4. Modeling, Reconstruction and Tracking for Face Recognition
5. 3D Face Recognition
6. Introduction to Iris Biometrics
7. Voice Biometrics: Speaker Verification and Identification
8. Introduction to Hand Biometrics
9. Multibiometrics
10. Hidden Biometrics
11. Performance Evaluation of Biometric Systems
12. Classification Techniques for Biometrics
13. Data Cryptography
14. Visual Data Protection
15. Biometrics in Forensics

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Introduction to Random Signals and Applied Kalman Filtering: with Matlab Exercises

Book Description
Advances in computers and personal navigation systems have greatly expanded the applications of Kalman filters. A Kalman filter uses information about noise and system dynamics to reduce uncertainty from noisy measurements. Common applications of Kalman filters include such fast-growing fields as autopilot systems, battery state of charge (SoC) estimation, brain-computer interface, dynamic positioning, inertial guidance systems, radar tracking, and satellite navigation systems.

Table of Contents
PART 1: RANDOM SIGNALS BACKGROUND
Chapter 1 Probability and Random Variables: A Review
Chapter 2 Mathematical Description of Random Signals
Chapter 3 Linear Systems Response, State-space Modeling and Monte Carlo Simulation
PART 2: KALMAN FILTERING AND APPLICATIONS
Chapter 4 Discrete Kalman Filter Basics
Chapter 5 Intermediate Topics on Kalman Filtering
Chapter 6 Smoothing and Further Intermediate Topics
Chapter 7 Linearization, Nonlinear Filtering and Sampling Bayesian Filters
Chapter 8 the "Go-Free" Concept, Complementary Filter and Aided Inertial Examples
Chapter 9 Kalman Filter Applications to the GPS and Other Navigation Systems

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Small Signal Audio Design by Douglas Self 1st and 2nd Eds

Book Description
Small Signal Audio Design is a unique guide to the design of high-quality circuitry for preamplifiers, mixing consoles, and a host of other signal-processing devices. Learn to use inexpensive and readily available parts to obtain state-of-the-art performance in all the vital parameters of noise, distortion, crosstalk and so on. Focusing mainly on preamplifiers and mixers this practical handbook gives you an extensive repertoire of circuits that can be put together to make almost any type of audio system.

Table of Contents
CHAPTER 1 - The Basics
CHAPTER 2 - Components
CHAPTER 3 - Discrete Transistor Circuitry
CHAPTER 4 - Op-Amps and Their Properties
CHAPTER 5 - Filters
CHAPTER 6 - Preamplifier Architectures
CHAPTER 7 - Moving-Magnet Disc Inputs
CHAPTER 8 - Moving-Coil Head Amplifiers
CHAPTER 9 - Volume and Balance Controls
CHAPTER 10 - Tone Controls and Equalizers
CHAPTER 11 - A Complete Preamplifier
CHAPTER 12 - Mixer Architectures
CHAPTER 13 - Microphone Preamplifiers
CHAPTER 14 - Line Inputs
CHAPTER 15 - Line Outputs
CHAPTER 16 - Signal Switching
CHAPTER 17 - Mixer Subsystems
CHAPTER 18 - Level Indication and Metering
CHAPTER 19 - Level Control and Special Circuits
CHAPTER 20 - Power Supplies
CHAPTER 21 - Interfacing with the Digital Domain

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Signals, Systems and Transforms (4th. Ed.)

Book Description
This book is ideal for electrical and computer engineers. The text provides a clear, comprehensive presentation of both the theory and applications in signals, systems, and transforms. It presents the mathematical background of signals and systems, including the Fourier transform, the Fourier series, the Laplace transform, the discrete-time and the discrete Fourier transforms, and the z-transform. The text integrates MATLAB examples into the presentation of signal and system theory and applications.

Table of Contents
1 INTRODUCTION
2 CONTINUOUS-TIME SIGNALS AND SYSTEMS
3 CONTINUOUS-TIME LINEAR TIME-INVARIANT SYSTEMS
4 FOURIER SERIES
5 THE FOURIER TRANSFORM
6 APPLICATIONS OF THE FOURIER TRANSFORM
7 THE LAPLACE TRANSFORM
8 STATE VARIABLES FOR CONTINUOUS-TIME SYSTEMS
9 DISCRETE-TIME SIGNALS AND SYSTEMS
10 DISCRETE-TIME LINEAR TIME-INVARIANT SYSTEMS
11 THE z-TRANSFORM
12 FOURIER TRANSFORMS OF DISCRETE-TIME SIGNALS
13 STATE VARIABLES FOR DISCRETE-TIME SYSTEMS

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Digital Signal Processing: Principles, Algorithms, and Applications

	Title:	Digital Signal Processing: Principles, Algorithms, and Applications
	Authors:	John G. Proakis, Dimitris G. Manolakis
	Edition:	4th - 2006
	Publisher:	Pearson
	Pages:	1104
	Language:	English
	ISBN-10	0131873741
	ISBN-13	9780131873742
	Format:	DJVU + Solution Manual (SM)
	Size (MB):	12 (DJVU), 3 (SM)
	Book Description: This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science. The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing. Table of Contents: Introduction Discrete-Time Signals And Systems The Z-Transform And Its Application To The Analysis Of LTI Systems Frequency Analysis Of Signals And Systems Frequency Domain Analysis Of Lti Systems Sampling And Reconstruction Of Signals The Discrete Fourier Transform: Its Properties and Applications Efficient Computation Of The Dft: Fast Fourier Transform Algorithms Implementation Of Discrete-Time Systems Design Of Digital Filers Multirate Digital Signal Processing Linear Prediction And Optimum Linear Filters Adaptive Filters Power Spectrum Estimation Copyright Disclaimer: This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.

Classification, Parameter Estimation and State Estimation

Book Description
Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MATLAB. 'Prtools' is a powerful MATLAB toolbox for pattern recognition and is written and owned by one of the co-authors, B. Duin of the Delft University of Technology.

Table of Contents
Chapter 1 Introduction
Chapter 2 Detection and Classification
Chapter 3 Parameter Estimation
Chapter 4 State Estimation
Chapter 5 Supervised Learning
Chapter 6 Feature Extraction and Selection
Chapter 7 Unsupervised Learning
Chapter 8 State Estimation in Practice
Chapter 9 Worked out Examples

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Digital Signal Processing Using Matlab V.4 - Proakis and Ingle

Book Description
In this supplementary text, 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.

Table of Contents
1. INTRODUCTION.
2. DISCRETE-TIME SIGNALS AND SYSTEMS.
3. THE DISCRETE-TIME FOURIER ANALYSIS.
4. THE z-TRANSFORM.
5. THE DISCRETE FOURIER TRANSFORM.
6. DIGITAL FILTER STRUCTURES.
7. FIR FILTER DESIGN. Preliminaries.
8. IIR FILTER DESIGN.
9. APPLICATIONS IN ADAPTIVE FILTERING.
10. APPLICATIONS IN COMMUNICATIONS.

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Adaptive Filtering Primer with MATLAB - Free PDF

Book Description
Presents in simple terms the fundamentals of a complicated area of signal processing. Provides a self-contained, easily understood introduction to Wiener filtering, the LMS algorithm, and the least-squares approach. Demonstrates practical application through MATLAB® programs and computer experiments. Includes abundant problems along with detailed solutions, hints, or suggestions for solving every problem in the book. Offers an appendix on matrix computation.

Table of Contents
INTRODUCTION
DISCRETE-TIME SIGNAL PROCESSING
RANDOM VARIABLES, SEQUENCES, AND STOCHASTIC PROCESSES
WIENER FILTERS
EIGENVALUES OF RX - PROPERTIES OF THE ERROR SURFACE
NEWTON AND STEEPEST-DESCENT METHOD
THE LEAST MEAN-SQUARE (LMS) ALGORITHM
VARIATIONS OF LMS ALGORITHMS
LEAST SQUARES AND RECURSIVE LEAST-SQUARES SIGNAL PROCESSING

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Biomedical Signal Processing and Signal Modeling

Book Description
A biomedical engineering perspective on the theory, methods, and applications of signal processing This book provides a unique framework for understanding signal processing of biomedical signals and what it tells us about signal sources and their behavior in response to perturbation. Using a modeling-based approach, the author shows how to perform signal processing by developing and manipulating a model of the signal source, providing a logical, coherent basis for recognizing signal types and for tackling the special challenges posed by biomedical signals-including the effects of noise on the signal, changes in basic properties, or the fact that these signals contain large stochastic components and may even be fractal or chaotic. Each chapter begins with a detailed biomedical example, illustrating the methods under discussion and highlighting the interconnection between the theoretical concepts and applications. The author has enlisted experts from numerous subspecialties in biomedical engineering to help develop these examples and has made most examples available as Matlab or Simulink files via anonymous ftp. Without the need for a background in electrical engineering, readers will become acquainted with proven techniques for analyzing biomedical signals and learn how to choose the appropriate method for a given application.

Table of Contents
The Nature of Biomedical Signals.
Memory and Correlation.
The Impulse Response.
Frequency Response.
Modeling Continuous-Time Signals as Sums of Sine Waves.
Responses of Linear Continuous-Time Filters to Arbitrary Inputs.
Modeling Signals as Sums of Discrete-Time Sine Waves.
Noise Removal and Signal Compensation.
Modeling Stochastic Signals as Filtered White Noise.
Scaling and Long-Term Memory.
Nonlinear Models of Signals.
Assessing Stationarity and Reproducibility.

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