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Understanding Digital Signal Processing, 3rd Edition

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Understanding Digital Signal Processing, 3rd Edition


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  • Readable, intuitive, example-rich, and accurate: helps readers fully grasp the basics and quickly move on to sophisticated techniques
  • Includes extensive new coverage of FIR and IIR filter analysis, multirate processing, digital differentiators, integrators, matched filters, and much more
  • Now contains end-of-chapter problems to support college instruction and professional self-study
  • This classic and best seller digital signal processing book for practicing engineers has been updated to include the latest techniques making it an even more practical real-work DSP book, but its most significant change is the inclusion of end of chapter homework problems that will enable college and university instructors to adopt it as a textbook.
  • Description

    • Copyright 2011
    • Dimensions: 7" x 9-1/8"
    • Pages: 992
    • Edition: 3rd
    • Book
    • ISBN-10: 0-13-702741-9
    • ISBN-13: 978-0-13-702741-5

    Amazon.com’s Top-Selling DSP Book for Seven Straight Years—Now Fully Updated!

    Understanding Digital Signal Processing, Third Edition, is quite simply the best resource for engineers and other technical professionals who want to master and apply today’s latest DSP techniques. Richard G. Lyons has updated and expanded his best-selling second edition to reflect the newest technologies, building on the exceptionally readable coverage that made it the favorite of DSP professionals worldwide. He has also added hands-on problems to every chapter, giving students even more of the practical experience they need to succeed.

    Comprehensive in scope and clear in approach, this book achieves the perfect balance between theory and practice, keeps math at a tolerable level, and makes DSP exceptionally accessible to beginners without ever oversimplifying it. Readers can thoroughly grasp the basics and quickly move on to more sophisticated techniques.

    This edition adds extensive new coverage of FIR and IIR filter analysis techniques, digital differentiators, integrators, and matched filters. Lyons has significantly updated and expanded his discussions of multirate processing techniques, which are crucial to modern wireless and satellite communications. He also presents nearly twice as many DSP Tricks as in the second edition—including techniques even seasoned DSP professionals may have overlooked.

    Coverage includes

    • New homework problems that deepen your understanding and help you apply what you’ve learned
    • Practical, day-to-day DSP implementations and problem-solving throughout
    • Useful new guidance on generalized digital networks, including discrete differentiators, integrators, and matched filters
    • Clear descriptions of statistical measures of signals, variance reduction by averaging, and real-world signal-to-noise ratio (SNR) computation
    • A significantly expanded chapter on sample rate conversion (multirate systems) and associated filtering techniques
    • New guidance on implementing fast convolution, IIR filter scaling, and more
    • Enhanced coverage of analyzing digital filter behavior and performance for diverse communications and biomedical applications
    • Discrete sequences/systems, periodic sampling, DFT, FFT, finite/infinite impulse response filters, quadrature (I/Q) processing, discrete Hilbert transforms, binary number formats, and much more

    Sample Content

    Online Sample Chapter

    Understanding Digital Signal Processing: Discrete Sequences and Systems

    Sample Pages

    Download the sample pages (includes Chapter 1 and Index)

    Table of Contents

    Preface      xv

    About the Author      xxiii

    Chapter 1: Discrete Sequences and Systems      1

    1.1 Discrete Sequences and their Notation   2

    1.2 Signal Amplitude, Magnitude, Power   8

    1.3 Signal Processing Operational Symbols   10

    1.4 Introduction to Discrete Linear Time-Invariant Systems   12

    1.5 Discrete Linear Systems   12

    1.6 Time-Invariant Systems   17

    1.7 The Commutative Property of Linear Time-Invariant Systems   18

    1.8 Analyzing Linear Time-Invariant Systems   19

    References   21

    Chapter 1 Problems   23

    Chapter 2: Periodic Sampling      33

    2.1 Aliasing: Signal Ambiguity in the Frequency Domain   33

    2.2 Sampling Lowpass Signals   38

    2.3 Sampling Bandpass Signals   42

    2.4 Practical Aspects of Bandpass Sampling   45

    References   49

    Chapter 2 Problems   50

    Chapter 3: The Discrete Fourier Transform     59

    3.1 Understanding the DFT Equation   60

    3.2 DFT Symmetry   73

    3.3 DFT Linearity   75

    3.4 DFT Magnitudes   75

    3.5 DFT Frequency Axis   77

    3.6 DFT Shifting Theorem   77

    3.7 Inverse DFT   80

    3.8 DFT Leakage   81

    3.9 Windows   89

    3.10 DFT Scalloping Loss   96

    3.11 DFT Resolution, Zero Padding, and Frequency-Domain Sampling   98

    3.12 DFT Processing Gain   102

    3.13 The DFT of Rectangular Functions   105

    3.14 Interpreting the DFT Using the Discrete-Time Fourier Transform   120

    References   124

    Chapter 3 Problems   125

    Chapter 4: The Fast Fourier Transform      135

    4.1 Relationship of the FFT to the DFT 136

    4.2 Hints on Using FFTs in Practice 137

    4.3 Derivation of the Radix-2 FFT Algorithm 141

    4.4 FFT Input/Output Data Index Bit Reversal 149

    4.5 Radix-2 FFT Butterfly Structures 151

    4.6 Alternate Single-Butterfly Structures 154

    References 158

    Chapter 4 Problems 160

    Chapter 5: Finite Impulse Response Filters      169

    5.1 An Introduction to Finite Impulse Response (FIR) Filters   170

    5.2 Convolution in FIR Filters   175

    5.3 Lowpass FIR Filter Design   186

    5.4 Bandpass FIR Filter Design   201

    5.5 Highpass FIR Filter Design   203

    5.6 Parks-McClellan Exchange FIR Filter Design Method   204

    5.7 Half-band FIR Filters   207

    5.8 Phase Response of FIR Filters   209

    5.9 A Generic Description of Discrete Convolution   214

    5.10 Analyzing FIR Filters   226

    References   235

    Chapter 5 Problems   238

    Chapter 6: Infinite Impulse Response Filters      253

    6.1 An Introduction to Infinite Impulse Response Filters   254

    6.2 The Laplace Transform   257

    6.3 The z-Transform   270

    6.4 Using the z-Transform to Analyze IIR Filters   274

    6.5 Using Poles and Zeros to Analyze IIR Filters   282

    6.6 Alternate IIR Filter Structures   289

    6.7 Pitfalls in Building IIR Filters   292

    6.8 Improving IIR Filters with Cascaded Structures   295

    6.9 Scaling the Gain of IIR Filters   300

    6.10 Impulse Invariance IIR Filter Design Method   303

    6.11 Bilinear Transform IIR Filter Design Method   319

    6.12 Optimized IIR Filter Design Method   330

    6.13 A Brief Comparison of IIR and FIR Filters   332

    References   333

    Chapter 6 Problems   336

    Chapter 7: Specialized Digital Networks and Filters      361

    7.1 Differentiators   361

    7.2 Integrators   370

    7.3 Matched Filters   376

    7.4 Interpolated Lowpass FIR Filters   381

    7.5 Frequency Sampling Filters: The Lost Art   392

    References   426

    Chapter 7 Problems   429

    Chapter 8: Quadrature Signals       439

    8.1 Why Care about Quadrature Signals?   440

    8.2 The Notation of Complex Numbers   440

    8.3 Representing Real Signals Using Complex Phasors   446

    8.4 A Few Thoughts on Negative Frequency   450

    8.5 Quadrature Signals in the Frequency Domain   451

    8.6 Bandpass Quadrature Signals in the Frequency Domain   454

    8.7 Complex Down-Conversion   456

    8.8 A Complex Down-Conversion Example   458

    8.9 An Alternate Down-Conversion Method   462

    References   464

    Chapter 8 Problems   465

    Chapter 9: The Discrete Hilbert Transform       479

    9.1 Hilbert Transform Definition   480

    9.2 Why Care about the Hilbert Transform?   482

    9.3 Impulse Response of a Hilbert Transformer   487

    9.4 Designing a Discrete Hilbert Transformer   489

    9.5 Time-Domain Analytic Signal Generation   495

    9.6 Comparing Analytical Signal Generation Methods   497

    References   498

    Chapter 9 Problems   499

    Chapter 10: Sample Rate Conversion       507

    10.1 Decimation   508

    10.2 Two-Stage Decimation   510

    10.3 Properties of Downsampling   514

    10.4 Interpolation   516

    10.5 Properties of Interpolation   518

    10.6 Combining Decimation and Interpolation   521

    10.7 Polyphase Filters   522

    10.8 Two-Stage Interpolation   528

    10.9 z-Transform Analysis of Multirate Systems   533

    10.10 Polyphase Filter Implementations   535

    10.11 Sample Rate Conversion by Rational Factors   540

    10.12 Sample Rate Conversion with Half-band Filters   543

    10.13 Sample Rate Conversion with IFIR Filters   548

    10.14 Cascaded Integrator-Comb Filters   550

    References   566

    Chapter 10 Problems   568

    Chapter 11: Signal Averaging      589

    11.1 Coherent Averaging   590

    11.2 Incoherent Averaging   597

    11.3 Averaging Multiple Fast Fourier Transforms   600

    11.4 Averaging Phase Angles   603

    11.5 Filtering Aspects of Time-Domain Averaging   604

    11.6 Exponential Averaging   608

    References   615

    Chapter 11 Problems   617

    Chapter 12: Digital Data Formats and their Effects      623

    12.1 Fixed-Point Binary Formats   623

    12.2 Binary Number Precision and Dynamic Range   632

    12.3 Effects of Finite Fixed-Point Binary Word Length   634

    12.4 Floating-Point Binary Formats   652

    12.5 Block Floating-Point Binary Format   658

    References   658

    Chapter 12 Problems   661

    Chapter 13: Digital Signal Processing Tricks        671

    13.1 Frequency Translation without Multiplication   671

    13.2 High-Speed Vector Magnitude Approximation   679

    13.3 Frequency-Domain Windowing   683

    13.4 Fast Multiplication of Complex Numbers   686

    13.5 Efficiently Performing the FFT of Real Sequences   687

    13.6 Computing the Inverse FFT Using the Forward FFT   699

    13.7 Simplified FIR Filter Structure   702

    13.8 Reducing A/D Converter Quantization Noise   704

    13.9 A/D Converter Testing Techniques   709

    13.10 Fast FIR Filtering Using the FFT   716

    13.11 Generating Normally Distributed Random Data   722

    13.12 Zero-Phase Filtering   725

    13.13 Sharpened FIR Filters   726

    13.14 Interpolating a Bandpass Signal   728

    13.15 Spectral Peak Location Algorithm   730

    13.16 Computing FFT Twiddle Factors   734

    13.17 Single Tone Detection   737

    13.18 The Sliding DFT   741

    13.19 The Zoom FFT   749

    13.20 A Practical Spectrum Analyzer   753

    13.21 An Efficient Arctangent Approximation   756

    13.22 Frequency Demodulation Algorithms   758

    13.23 DC Removal   761

    13.24 Improving Traditional CIC Filters   765

    13.25 Smoothing Impulsive Noise   770

    13.26 Efficient Polynomial Evaluation   772

    13.27 Designing Very High-Order FIR Filters   775

    13.28 Time-Domain Interpolation Using the FFT   778

    13.29 Frequency Translation Using Decimation   781

    13.30 Automatic Gain Control (AGC)   783

    13.31 Approximate Envelope Detection   784

    13.32 AQuadrature Oscillator   786

    13.33 Specialized Exponential Averaging   789

    13.34 Filtering Narrowband Noise Using Filter Nulls   792

    13.35 Efficient Computation of Signal Variance   797

    13.36 Real-time Computation of Signal Averages and Variances   799

    13.37 Building Hilbert Transformers from Half-band Filters   802

    13.38 Complex Vector Rotation with Arctangents   805

    13.39 An Efficient Differentiating Network   810

    13.40 Linear-Phase DC-Removal Filter   812

    13.41 Avoiding Overflow in Magnitude Computations   815

    13.42 Efficient Linear Interpolation   815

    13.43 Alternate Complex Down-conversion Schemes   816

    13.44 Signal Transition Detection   820

    13.45 Spectral Flipping around Signal Center Frequency   821

    13.46 Computing Missing Signal Samples   823

    13.47 Computing Large DFTs Using Small FFTs   826

    13.48 Computing Filter Group Delay without Arctangents   830

    13.49 Computing a Forward and Inverse FFT Using a Single FFT   831

    13.50 Improved Narrowband Lowpass IIR Filters   833

    13.51 A Stable Goertzel Algorithm   838

    References   840

    Appendix A: The Arithmetic of Complex Numbers       847

    A.1 Graphical Representation of Real and Complex Numbers   847

    A.2 Arithmetic Representation of Complex Numbers   848

    A.3 Arithmetic Operations of Complex Numbers   850

    A.4 Some Practical Implications of Using Complex Numbers   856

    Appendix B: Closed Form of a Geometric Series       859

    Appendix C: Time Reversal and the DFT       863

    Appendix D: Mean, Variance, and Standard Deviation       867

    D.1 Statistical Measures   867

    D.2 Statistics of Short Sequences   870

    D.3 Statistics of Summed Sequences   872

    D.4 Standard Deviation (RMS) of a Continuous Sinewave   874

    D.5 Estimating Signal-to-Noise Ratios   875

    D.6 The Mean and Variance of Random Functions   879

    D.7 The Normal Probability Density Function   882

    Appendix E: Decibels (DB and DBM)       885

    E.1 Using Logarithms to Determine Relative Signal Power   885

    E.2 Some Useful Decibel Numbers   889

    E.3 Absolute Power Using Decibels   891

    Appendix F: Digital Filter Terminology       893

    Appendix G: Frequency Sampling Filter Derivations       903

    G.1 Frequency Response of a Comb Filter   903

    G.2 Single Complex FSF Frequency Response   904

    G.3 Multisection Complex FSF Phase   905

    G.4 Multisection Complex FSF Frequency Response   906

    G.5 Real FSF Transfer Function   908

    G.6 Type-IV FSF Frequency Response   910

    Appendix H: Frequency Sampling Filter Design Tables      913

    Appendix I: Computing Chebyshev Window Sequences        927

    I.1 Chebyshev Windows for FIR Filter Design   927

    I.2 Chebyshev Windows for Spectrum Analysis   929

    Index        931


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