Table of Contents:

Chapter 1: Discrete Sequences and Systems

• 1.1 Discrete Sequences and their Notation

• 1.2 Signal Amplitude, Magnitude, Power

• 1.3 Signal Processing Operational Symbols

• 1.4 Introduction to Discrete Linear Time-Invariant Systems

• 1.5 Discrete Linear Systems

• 1.6 Time-Invariant Systems

• 1.7 The Commutative Property of Linear Time-Invariant Systems

• 1.8 Analyzing Linear Time-Invariant Systems

Chapter 2: Periodic Sampling

• 2.1 Aliasing: Signal Ambiguity in the Frequency Domain

• 2.2 Sampling Lowpass Signals

• 2.3 Sampling Bandpass Signals

• 2.4 Practical Aspects of Bandpass Sampling

Chapter 3: The Discrete Fourier Transform

• 3.1 Understanding the DFT Equation

• 3.2 DFT Symmetry

• 3.3 DFT Linearity

• 3.4 DFT Magnitudes

• 3.5 DFT Frequency Axis

• 3.6 DFT Shifting Theorem

• 3.7 Inverse DFT

• 3.8 DFT Leakage

• 3.9 Windows

• 3.10 DFT Scalloping Loss

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

• 3.12 DFT Processing Gain

• 3.13 The DFT of Rectangular Functions

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

Chapter 4: The Fast Fourier Transform

• 4.1 Relationship of the FFT to the DFT

• 4.2 Hints on Using FFTs in Practice

• 4.3 Derivation of the Radix-2 FFT Algorithm

• 4.4 FFT Input/Output Data Index Bit Reversal

• 4.5 Radix-2 FFT Butterfly Structures

• 4.6 Alternate Single-Butterfly Structures

Chapter 5: Finite Impulse Response Filters

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

• 5.2 Convolution in FIR Filters

• 5.3 Lowpass FIR Filter Design

• 5.4 Bandpass FIR Filter Design

• 5.5 Highpass FIR Filter Design

• 5.6 Parks-McClellan Exchange FIR Filter Design Method

• 5.7 Half-band FIR Filters

• 5.8 Phase Response of FIR Filters

• 5.9 A Generic Description of Discrete Convolution

• 5.10 Analyzing FIR Filters

Chapter 6: Infinite Impulse Response Filters

• 6.1 An Introduction to Infinite Impulse Response Filters

• 6.2 The Laplace Transform

• 6.3 The z-Transform

• 6.4 Using the z-Transform to Analyze IIR Filters

• 6.5 Using Poles and Zeros to Analyze IIR Filters

• 6.6 Alternate IIR Filter Structures

• 6.7 Pitfalls in Building IIR Filters

• 6.8 Improving IIR Filters with Cascaded Structures

• 6.9 Scaling the Gain of IIR Filters

• 6.10 Impulse Invariance IIR Filter Design Method

• 6.11 Bilinear Transform IIR Filter Design Method

• 6.12 Optimized IIR Filter Design Method

• 6.13 A Brief Comparison of IIR and FIR Filters

Chapter 7: Specialized Digital Networks and Filters

• 7.1 Differentiators

• 7.2 Integrators

• 7.3 Matched Filters

• 7.4 Interpolated Lowpass FIR Filters

• 7.5 Frequency Sampling Filters: The Lost Art

Chapter 8: Quadrature Signals

• 8.1 Why Care about Quadrature Signals?

• 8.2 The Notation of Complex Numbers

• 8.3 Representing Real Signals Using Complex Phasors

• 8.4 A Few Thoughts on Negative Frequency

• 8.5 Quadrature Signals in the Frequency Domain

• 8.6 Bandpass Quadrature Signals in the Frequency Domain

• 8.7 Complex Down-Conversion

• 8.8 A Complex Down-Conversion Example

• 8.9 An Alternate Down-Conversion Method

Chapter 9: The Discrete Hilbert Transform

• 9.1 Hilbert Transform Definition

• 9.2 Why Care about the Hilbert Transform?

• 9.3 Impulse Response of a Hilbert Transformer

• 9.4 Designing a Discrete Hilbert Transformer

• 9.5 Time-Domain Analytic Signal Generation

• 9.6 Comparing Analytical Signal Generation Methods

Chapter 10: Sample Rate Conversion

• 10.1 Decimation

• 10.2 Two-Stage Decimation

• 10.3 Properties of Downsampling

• 10.4 Interpolation

• 10.5 Properties of Interpolation

• 10.6 Combining Decimation and Interpolation

• 10.7 Polyphase Filters

• 10.8 Two-Stage Interpolation

• 10.9 z-Transform Analysis of Multirate Systems

• 10.10 Polyphase Filter Implementations

• 10.11 Sample Rate Conversion by Rational Factors

• 10.12 Sample Rate Conversion with Half-band Filters

• 10.13 Sample Rate Conversion with IFIR Filters

• 10.14 Cascaded Integrator-Comb Filters

Chapter 11: Signal Averaging

• 11.1 Coherent Averaging

• 11.2 Incoherent Averaging

• 11.3 Averaging Multiple Fast Fourier Transforms

• 11.4 Averaging Phase Angles

• 11.5 Filtering Aspects of Time-Domain Averaging

• 11.6 Exponential Averaging

Chapter 12: Digital Data Formats and their Effects

• 12.1 Fixed-Point Binary Formats

• 12.2 Binary Number Precision and Dynamic Range

• 12.3 Effects of Finite Fixed-Point Binary Word Length

• 12.4 Floating-Point Binary Formats

• 12.5 Block Floating-Point Binary Format8

Chapter 13: Digital Signal Processing Tricks

• 13.1 Frequency Translation without Multiplication

• 13.2 High-Speed Vector Magnitude Approximation

• 13.3 Frequency-Domain Windowing

• 13.4 Fast Multiplication of Complex Numbers

• 13.5 Efficiently Performing the FFT of Real Sequences

• 13.6 Computing the Inverse FFT Using the Forward FFT

• 13.7 Simplified FIR Filter Structure

• 13.8 Reducing A/D Converter Quantization Noise

• 13.9 A/D Converter Testing Techniques

• 13.10 Fast FIR Filtering Using the FFT

• 13.11 Generating Normally Distributed Random Data

• 13.12 Zero-Phase Filtering

• 13.13 Sharpened FIR Filters

• 13.14 Interpolating a Bandpass Signal

• 13.15 Spectral Peak Location Algorithm

• 13.16 Computing FFT Twiddle Factors

• 13.17 Single Tone Detection

• 13.18 The Sliding DFT

• 13.19 The Zoom FFT

• 13.20 A Practical Spectrum Analyzer

• 13.21 An Efficient Arctangent Approximation

• 13.22 Frequency Demodulation Algorithms

• 13.23 DC Removal

• 13.24 Improving Traditional CIC Filters

• 13.25 Smoothing Impulsive Noise

• 13.26 Efficient Polynomial Evaluation

• 13.27 Designing Very High-Order FIR Filters

• 13.28 Time-Domain Interpolation Using the FFT

• 13.29 Frequency Translation Using Decimation

• 13.30 Automatic Gain Control (AGC)

• 13.31 Approximate Envelope Detection

• 13.32 AQuadrature Oscillator

• 13.33 Specialized Exponential Averaging

• 13.34 Filtering Narrowband Noise Using Filter Nulls

• 13.35 Efficient Computation of Signal Variance

• 13.36 Real-time Computation of Signal Averages and Variances

• 13.37 Building Hilbert Transformers from Half-band Filters

• 13.38 Complex Vector Rotation with Arctangents

• 13.39 An Efficient Differentiating Network

• 13.40 Linear-Phase DC-Removal Filter

• 13.41 Avoiding Overflow in Magnitude Computations

• 13.42 Efficient Linear Interpolation

• 13.43 Alternate Complex Down-conversion Schemes

• 13.44 Signal Transition Detection

• 13.45 Spectral Flipping around Signal Center Frequency

• 13.46 Computing Missing Signal Samples

• 13.47 Computing Large DFTs Using Small FFTs

• 13.48 Computing Filter Group Delay without Arctangents

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

• 13.50 Improved Narrowband Lowpass IIR Filters

• 13.51 A Stable Goertzel Algorithm

Appendix A: The Arithmetic of Complex Numbers

Appendix B: Closed Form of a Geometric Series

Appendix C: Time Reversal and the DFT

Appendix D: Mean, Variance, and Standard Deviation

Appendix E: Decibels (DB and DBM)

Appendix F: Digital Filter Terminology

Appendix G: Frequency Sampling Filter Derivations

Appendix H: Frequency Sampling Filter Design Tables

Appendix I: Computing Chebyshev Window Sequences

　本書其它內容…