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Digital Signal Processing Using Matlab by Vinay K Ingle

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Synopsis
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.


Product Identifiers
ISBN-10
0495073113
ISBN-13
9780495073116

Key Details
Author
John G. Proakis, Vinay K. Ingle
Number Of Pages
512 pages
Format
EBOOK
Publication Date
2006-08-10
Language
English
Publisher
Course Technology
Publication Year
2006


Additional Details
Edition Number
2
Copyright Date
2007
Illustrated
Yes

Target Audience
Group
College Audience


Classification Method
Dewey Decimal
621.3/822/028555
Dewey Edition
22


Table Of Content
Chapter 1 - Introduction 1.1 Overview of Digital Signal Processing 1.2 A Few Words about MATLAB® Chapter 2 - Discrete-time Signals and Systems 2.1 Discrete-time Signals 2.2 Discrete Systems 2.3 Convolution 2.4 Difference Equations 2.5 Problems Chapter 3 - The Discrete-time Fourier Analysis 3.1 The discrete-time Fourier Transform 3.2 The Properties of the DTFT 3.3 The Frequency Domain Representation of LSI Systems 3.4 Sampling and Reconstruction of Analog Signals 3.5 Problems Chapter 4 - The z-Transform 4.1 The Bilateral z-Transform 4.2 Important Properties of the z-Transform 4.3 Inversion of the z-Transform 4.4 System Representation in the z-Domain 4.5 Solutions of the Difference Equations 4.6 Problems Chapter 5 - The Discrete Fourier Transform 5.1 The Discrete Fourier Series 5.2 Sampling and Reconstruction in the z-Domain 5.3 The Discrete Fourier Transform 5.4 Properties of the Discrete Fourier Transform 5.5 Linear Convolution using the DFT 5.6 Circulant matrices 5.7 The Fast Fourier Transform 5.8 Problems Chapter 6 - Digital Filter Structures 6.1 Basic Elements 6.2 IIR Filter Structures 6.3 FIR Filter Structures 6.4 Lattice Structures 6.5 Problems Chapter 7 - FIR Filter Design 7.1 Preliminaries 7.2 Properties of Linear Phase FIR Filters 7.3 Window Design Techniques 7.4 Frequency Sampling Design Techniques 7.5 Optimal Equiripple Design Technique 7.6 Problems Chapter 8 - IIR Filter Design 8.1 Some preliminaries 8.2 Characteristics of Prototype Analog Filters 8.3 Analog-to-Digital Filter Transformations 8.4 Lowpass Filter Design using MATLAB 8.5 Frequency-band Transformations 8.6 Comparison of FIR vs. IIR Filters 8.7 Problems Chapter 9 - Finite Word-Length Effects 9.1 Overview 9.2 Representation of Numbers 9.3 The Process of Quantization and Error Characterization 9.4 Quantization of Filter Coefficients 9.5 Analysis of A/D Quantization Noise 9.6 Round-Off Effects in IIR Digital Filters 9.7 Round-Off Noise in FIR Filter Realizations 9.8 Summary 9.9 Problems Chapter 10 - Sampling Rate Conversion 10.1 Introduction 10.2 Decimation by a Factor D 10.3 Interpolation by a Factor 10.4 Sampling Rate Conversion by a Rational Factor I/D 10.5 FIR Filter Designs for Sample Rate Conversion 10.6 FIR Filter Structures for Sampling-Rate Conversion 10.7 Summary 10.8 Problems Chapter 11 - Applications in Adaptive Filtering 11.1 LMS Algorithm for Coefficient Adjustment 11.2 System Identification or System Modeling 11.3 Suppression of Narrowband Interference in a Wideband Signal 11.4 Adaptive Line Enhancement 11.5 Adaptive Channel Equalization 11.6 Summary Chapter 12 - Applications in Communications 12.1 Pulse Code Modulation 12.2 Differential PCM (DPCM) 12.3 Adaptive PCM and DPCM (ADPCM) 12.4 Delta Modulation (DM) 12.5 Linear Predictive Coding (LPC) of Speech 12.6 Dual-Tone Multifrequency (DTMF) Signals 12.7 Binary Digital Communications 12.8 Spread Spectrum Communications 12.9 SummaryChapter 1 ? Introduction 1.1 Overview of Digital Signal Processing 1.2 A Few Words about MATLAB® Chapter 2 - Discrete-time Signals and Systems 2.1 Discrete-time Signals 2.2 Discrete Systems 2.3 Convolution 2.4 Difference Equations 2.5 Problems Chapter 3 - The Discrete-time Fourier Analysis 3.1 The discrete-time Fourier Transform 3.2 The Properties of the DTFT 3.3 The Frequency Domain Representation of LSI Systems 3.4 Sampling and Reconstruction of Analog Signals 3.5 Problems Chapter 4 - The z-Transform 4.1 The Bilateral z-Transform 4.2 Important Properties of the z-Transform 4.3 Inversion of the z-Transform 4.4 System Representation in the z-Domain 4.5 Solutions of the Difference Equations 4.6 Problems Chapter 5 - The Discrete Fourier Transform 5.1 The Discrete Fourier Series 5.2 Sampling and Reconstruction in the z-Domain 5.3 The Discrete Fourier Transform 5.4 Properties of the Discrete Fourier Transform 5.5 Linear Convolution using the DFT 5.6 Circulant matrices 5.7 The Fast Fourier Transform 5.8 Problems Chapter 6 - Digital Filter Structures 6.1 Basic Elements 6.2 IIR Filter Structures 6.3 FIR Filter Structures 6.4 Lattice Structures 6.5 Problems Chapter 7 - FIR Filter Design 7.1 Preliminaries 7.2 Properties of Linear Phase FIR Filters 7.3 Window Design Techniques 7.4 Frequency Sampling Design Techniques 7.5 Optimal Equiripple Design Technique 7.6 Problems Chapter 8 - IIR Filter Design 8.1 Some preliminaries 8.2 Characteristics of Prototype Analog Filters 8.3 Analog-to-Digital Filter Transformations 8.4 Lowpass Filter Design using MATLAB 8.5 Frequency-band Transformations 8.6 Comparison of FIR vs. IIR Filters 8.7 Problems Chapter 9 - Finite Word-Length Effects 9.1 Overview 9.2 Representation of Numbers 9.3 The Process of Quantization and Error Characterization 9.4 Quantization of Filter Coefficients 9.5 Analysis of A/D Quantization Noise 9.6 Round-Off Effects in IIR Digital Filters 9.7 Round-Off Noise in FIR Filter Realizations 9.8 Summary 9.9 Problems Chapter 10 - Sampling Rate Conversion 10.1 Introduction 10.2 Decimation by a Factor D 10.3 Interpolation by a Factor 10.4 Sampling Rate Conversion by a Rational Factor I/D 10.5 FIR Filter Designs for Sample Rate Conversion 10.6 FIR Filter Structures for Sampling-Rate Conversion 10.7 Summary 10.8 Problems Chapter 11 - Applications in Adaptive Filtering 11.1 LMS Algorithm for Coefficient Adjustment 11.2 System Identification or System Modeling 11.3 Suppression of Narrowband Interference in a Wideband Signal 11.4 Adaptive Line Enhancement 11.5 Adaptive Channel Equalization 11.6 Summary Chapter 12 - Applications in Communications 12.1 Pulse Code Modulation 12.2 Differential PCM (DPCM) 12.3 Adaptive PCM and DPCM (ADPCM) 12.4 Delta Modulation (DM) 12.5 Linear Predictive Coding (LPC) of Speech 12.6 Dual-Tone Multifrequency (DTMF) Signals 12.7 Binary Digital Communications 12.8 Spread Spectrum Communications 12.9 Summary.
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