Richard G. Lyons

Understanding Digital Signal Processing (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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

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Produktdetails

• Verlag: Pearson ITP
• Seitenzahl: 992
• Altersempfehlung: ab 18 Jahre
• Erscheinungstermin: 1. November 2010
• Englisch
• ISBN-13: 9780137028528
• Artikelnr.: 52467789

Autorenporträt

Richard G. Lyons is a consulting Systems Engineer and lecturer with Besser Associates in Mountain View, California. He is author of the book "Understanding Digital Signal Processing", editor and contributor to the book "Streamlining Digital Signal Processing", and has authored numerous articles on DSP. Lyons has taught DSP at the University of California Santa Cruz Extension and recently received the IEEE Signal Processing Society's 2012 Educator of the Year award.

Inhaltsangabe

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