實時數字信號處理

定　價：￥49.80

作　者：	郭（Kuo,S.M.），李（Lee,B.h.）著
出版社：	清華大學出版社
叢編項：	基于TMS320C55X的實現應用和實驗
標　簽：	通信技術理論與基礎

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ISBN：	9787302077008	出版時間：	2003-12-01	包裝：	膠版紙
開本：	小16開	頁數：	496	字數：

內容簡介

　　“實時”功能是高性能數字信號處理器和DSP應用中面臨的最新挑戰(zhàn)。它的成功應用不僅需要徹底理解DSP理論，還要全面掌握實時DSP設計和應用技術。本書為讀者提供了一本非常實用的教材和參考書。本書具有如下特點：具有使用MATLAB，C和TMS320C55X匯編語言的豐富的習題和實驗，涵蓋了從基本概念到通信應用的所有內容。對數字信號處理的理論問題的討論，沒有復雜的理論推導，而且都是圍繞如何實現來展開的。指導如何選擇DSP芯片使之滿足各種不同應用的要求，如實時性約束、不同硬件選擇、定點或浮點器件等。[前言]本書的中文名字可以譯為《實時數字信號處理：基于TMS320C55X的實現、應用和實驗》。所謂"實時（Real-Time）實現"，是指一個實際的系統(tǒng)在人們聽覺、視覺或按任務要求所允許的時間范圍內能及時地完成對輸入信號的處理并將其輸出。例如，我們每天使用的手機、將要普及的數字電視等，都是實時的數字信號處理系統(tǒng)。要想在極短的時間內完成對信號的處理，一方面需要快速的算法、高效的編程，另一方面，則需要高性能的硬件支持。數字信號處理器（DSP）即是為實時實現數字信號處理任務而特殊設計的高性能的一類CPU。隨著信息科學和微電子技術的飛速發(fā)展，數字信號處理的理論及數字信號處理器已廣泛應用于通信、家電、航空航天、工業(yè)測量和控制、生物醫(yī)學工程及軍事等許許多多的領域。由于設計和實現一個實時的數字信號處理系統(tǒng)不僅需要系統(tǒng)地掌握信號處理的理論，而且要熟練地掌握DSP硬件的知識，因此，對設計者的要求是非常高、也是相當全面的。美國伊利諾斯大學電機工程系的SenM.Kuo教授和美國德州儀器公司的BobH.Lee博士合著的這本書為培養(yǎng)這一類人才提供了一本值得推薦的好教材。本書共分9章。第1章簡要介紹了實時數字信號處理系統(tǒng)的基本概念；第2章介紹了美國德州儀器公司最新推出的DSP芯片：TMS320C55X的結構及編程；第3章討論了DSP系統(tǒng)實時實現時的結構、量化及溢出等問題；第4～8章分別討論數字信號處理中的時域分析、頻域分析、FIR和IIR濾波器設計、快速傅里葉交換及自適應濾波等基本問題；第9章較為詳細地給出了DSP實時系統(tǒng)應用的例子，如信號產生（正弦信號、Chirp信號、噪聲等），自適應噪聲抵消及語音增強等。本書的特點是：1.全書以TMS320C55XDSP芯片為主線，系統(tǒng)地介紹了實時數字信號處理系統(tǒng)的設計和實現問題。2.本書雖然也以較大的篇幅討論了數字信號處理的理論問題，但目的都是圍繞著如何實現來展開的。3.本書每一章都安排了實驗舉例，或用C55的匯編語言，或用C語言來說明該章內容在DSP上的實現問題。通過這些實驗，讀者可以很快地掌握實時DSP系統(tǒng)的設計和實現問題。4.除第9章，本書每一章都附有豐富的習題。這些習題一部分是涉及信號處理的理論問題，但大部分是有關實時DSP系統(tǒng)實現的上機練習。5.本書沒有涉及復雜的理論推導，因此通俗易懂。本書可作為本科生、研究生的教材，也可作為工程技術人員的參考書。

作者簡介

暫缺《實時數字信號處理》作者簡介

圖書目錄

Preface
1 Introduction to Real-Time Digital Signal Procesing
1.1 Basic Elements of Real-Tiem DSP Systems
1.2 Input and Output Channels
1.2.1 Input Signal Conditioning
1.2.2 A/D Conversion
1.2.3 Sampling
1.2.4 Quantizing and Encoding
1.2.5 D/A Conversion
1.2.6 Imput/Output Devices
1.3 DSP Hardware
1.3.1 DSP Hardware Options
1.3.2 Fixed-and Floating -Point Devices
1.3.3 Real-Time Constraints
1.4 SDP System Decign
1.4.1 Algorithm Development
1.4.2 Selection of DSP Chips
1.4.3 Software Development
1.4.4 High-Level Software Development Tools
1.5 Experiments Using Code Composer Studio
1.5.1 Experiment IA-Using the CCS and the TMS320C55x Simulator
1.5.2 Experiment IB-Debugging Program on the CCS
1.5.3 Experiment IC-File Input and Output
1.5.4 Experiment ID-Code Efficiency Analysis
1.5.5 Experiment IE-General Extension Language
References
Exercises
2 Introduction to TMS320C55x Digital Signal Processor
2.1 Introduction
2.2 TMS320C55x Architecture
2.2.1 TMS320C55x Architecture Overview
2.2.2 TMS320C55x Buses
2.2.3 TMS320C55x Memory Map
2.3 Software Devielpment Tools
2.3.1 C Compiler
2.3.2 Assembler
2.3.3 Linker
2.3.4 Code Composer Studio
2.3.5 Assembly Statement Syntax
2.4 TMS320C55x Addressing Modes
2.4.1 Direct Addressing Mode
2.4.2 Indirect Addressing Mode
2.4.3 Absolute Addressing Mode
2.4.4 Memory-Mapped Register Addressing Mode
2.4.5 Register Bits Addressing Mode
2.4.6 Circular Addressing Mode
2.5 Pipeling and Parallelism
2.5.1 TMS320C55x Pipeline
2.5.2 Parallel Execution
2.6 TMS320C55x Instruction Set
2.6.1 Arithmetic Instruction
2.6.2 Logic and Bits Manipulation Imstructions
2.6.3 Move Instruction
2.6.4 Proram Flow Control Instructions
2.7 Mixed C and Assembly Language Programming
2.8 Experiments-Assembly Programming Basics
2.8.1 Experiment 2A-Interfacing C with Assembly Code
2.8.2 Experiment 2B-Addressing Mode Experiments
References
Exercises
3 SDP Fundamentals and Implementation Considerations
3.1 Digital Signals and Systems
3.1.1 Elemethary Digital Signals
3.1.2 Block Diagram Representation of Digital Systems
3.1.3 Impulse Response of Digital Systems
3.2 Introduction to Digital Filters
3.2.1 FIR Filters and Power Estimators
3.2.2 Response of Linear Systems
3.2.3 IIR Filters
3.3 Introduction to Random Variables
3.3.1 Reveiw of Probability and Random Variables
3.3.2 Operations on Random Variables
3.4 Fixed-Point Representation and Arithmetic
3.5 Quantization Errors
3.5.1 Input Quantization Noise
3.5.2 Coefficient Quantization Noise
3.5.3 Roundoff Noise
3.6 Overflow and Solutions
3.6.1 Saturation Arithmetic
3.6.2 Overflow Handling
3.6.3 Scaling of Signals
3.7 Implementation Procedure for Real-Time Applications
3.8 Experiments of Fixed-Point Implementations
3.8.1 Experiment 3S-Quantizatuion of Sinusoidal Signals
3.8.2 Experiment 3B-Quantization of Speech Signals
3.8.3 Experiment 3C-Overflow and Saturation Arithmetic
3.8.4 Experiment 3D-Quantization of Coefficients
3.8.5 Experiment 3E-Synthesizing Sine Function
References
Exercises
4 Frequency Analysis
4.1 Fourier Series and Transform
4.1.1 Fourier Series
4.1.2 Fourier Transform
4.2 The z-Transforms
4.2.1 Definitions and Basic Properties
4.2.2 Inverse z-Transform
4.3 System Concepts
4.3.1 Transfer Functions
4.3.2 Digital Filters
4.3.3 Poles and Zeros
4.3.4 Frequency Resposes
4.4 Discrete Fourier Transform
4.4.1 Discrete-Time Fourier Series and Transform
4.4.2 Aliasing and Folding
4.4.3 Discrete Fourier Transform
4.4.4 Fast Fourier Transform
4.5 Applicatins
4.5.1 Design of Simple Notch Filters
4.5.2 Analysis of Room Acoustics
4.6 Experiments Using the TMS320C55x
4.6.1 Experiment 4A-Twieddle Facotr Generation
4.6.2 Experiment 4B-Complex Data Operation
4.6.3 Experiment 4C-Implementation of DFT
4.6.4 Experiment 4D-Experiment Using Assembly Routines
References
Exercises
5 Design and Implementation of FIR Filters
5.1 Introduction to Degital Filters
5.1.1 Filter Characteristics
5.1.2 Filter Types
5.1.3 Filter Specifications
5.2 FIR Filtering
5.2.1 Linear Convolution
5.2.2 Some Simple FIR Filters
5.2.3 Linear Phase FIR Filters
5.2.4 Realization of FIR Filters
5.3 Design of FIR Filters
5.3.1 Filte Design Procedure
5.3.2 Fourier Series Method
5.3.3 Gibbs Phenomenon
5.3.4 Windows Functions
5.3.5 Frequency Sampling Method
5.4 Design of FIR Filters Using MATLAB
5.5 Implementation Considerations
5.5.1 Software Implementations
5.5.2 Quantization Effects in FIR Filters
5.6 Experiments Using the TML320C55x
5.6.1 Experiment 5A-Implementation of Block FIR Filter
5.6.2 Experiment 5B-Implementation of Symmetric FIR Filter
5.6.3 Experiment 5C-Implementation of FIR Filter Using Dual-MAC
References
Exercises
6 Design and Implementation of IIR Filters
6.1 Laplace Transform
6.1.1 Introduction to the Laplace Transform
6.1.2 Relationships between the Laplace and z-Transforms
6.1.3 Mapping Properties
6.2 Analog Filters
6.2.1 Introduction to Analog Filters
6.2.2 Characteristics of Analog Filters
6.2.3 Frequency Transforms
6.3 Design of IIR Filters
6.3.1 Review of IIR Filters
6.3.2 Impulse-Invariant Method
6.3.3 Bilinear Transform
6.3.4 Filter Design Using Bkinear Transform
6.4 Realization of IIR Filteras
6.4.1 Direct Forms
6.4.2 Cascade Form
6.4.3 Parallel Form
6.4.4 Realization Using MATLAB
6.5 Design of IIR Filters Using MATLAB
6.6 Implementation Consiserations
6.6.1 Stability
6.6.2 Finite-Precision Effects and Solutions
6.6.3 Software Implementations
6.6.4 Practical Applications
6.7 Software Developments and Experiments Using the TMS320C55x
6.7.1 Design of IIF Filter
6.7.2 Experiment 6A-Floating-Point C Implementation
6.7.3 Experiment 6B-Fixed-Point C Implementation Using Intrinsics
6.7.4 Experiment 6C-Fixed-Point C Programmig Considerations
6.7.5 Experiment 6D-Assembly Language Implementations
References
Exercises
7 Fast Fourier Transform and Its Applications
7.1 Discrete Fourier Transform
7.1.1 Definitions
7.1.2 Important Properties of DFT
7.1.3 Circular Convolution
7.2 Fast Fourier Transforms
7.2.1 Decimation-in-Time
7.2.2 Decimation-in-Frequency
7.2.3 Inverse Fast Fourier Transform
7.2.4 AMTLAB Implementations
7.3 Applications
7.3.1 Spectrum Estimation and Analysis
7.3.2 Spectral Leakage and Resolution
7.3.3 Power Density Spectrum
7.3.4 Fast Convolution
7.3.5 Spectrogram
7.4 Implementation Considerations
7.4.1 Computational Issues
7.4.2 Finite-Precistion Effects
7.5 Experiments Using the TMS320C55x
7.5.1 Experiment 7A-Radix-2 Complex FFT
7.5.2 Experiment 7B-Radix-2 Complex FFT Using Assembly Language
7.5.3 Experiment 7C-FFT and IFFT
7.5.4 Experiment 7D-Fast Convolution
References
Exercises
8 Adaptive Filtering
8.1 Introduction to Random Processes
8.1.1 Correlation Functions
8.1.2 Frequency-Domain Representations
8.2 Adaptive Filters
8.2.1 Introduction to Adaptive Filtering
8.2.2 Performance Function
8.2.3 Method of Steepest Descent
8.2.4 The LMS Alogrithm
8.3 Performance Analysis
8.3.1 Stability Constraint
8.3.2 Covergence Speed
8.3.3 Excess Mean0Square Error
8.4 Modified LMS Algorithms
8.4.1 Normalized LMS Algorithm
8.4.2 Leaky LMS Algorithm
8.5 Applications
8.5.1 Adaptive System Identification
8.5.2 Adaptive Linear Prediction
8.5.3 Adaptive Noies Cancellation
8.5.4 Adaptive Notch Filters
8.5.5 Adaptive Channel Equalization
8.6 Implementation Considerations
8.6.1 Computational Issues
8.6.2 Finite-Precision Effects
8.7 Experiments Using the TMS320C55x
8.7.1 Experiment 8A-Adaptive System Identification
8.7.2 Experiment 8B-Adaptive Predictor Using the Leaky LMS Algorithm
References
Exercises
9 Practical DSP Applications in Communications
9.1 Sinewave Generators and Applications
9.1.1 Lookup-Table Method
9.1.2 Linear Chirp Signal
9.1.3 DTMF Tone Generator
9.2 Noise Generators and Applications
9.2.1 Linear Congruential Sequence Generator
9.2.2 Pseudo-Random Binary Sequence Generator
9.2.3 Comfort Noise in Communication Systems
9.2.4 Off-Line System Modeling
9.3 DTMF Tone Detectiong
9.3.1 Specifications
9.3.2 Goertzel Algorithm
9.3.3 Implementation Considerations
9.4 Adaptive Echo Cancellation
9.4.1 Line Echoes
9.4.2 Adaptive Echo Canceler
9.4.3 Practical Considerations
9.4.4 Double-Tald Effects and Solutions
9.4.5 Residual Echo Cancellation
9.5 Introduction
9.5.1 Acoustic Echo Canceler
9.5.2 Implementation Considerations
9.5.3 Speech Enhancement Techniques
9.6 Noise Reduction Techniques
9.6.1 Spectral Subtraction Techniques
9.6.2 Implementation Considerations
9.6.3 Projects Using the TMS320C55x
9.7 Project Suggestions
9.7.1 Project Suggestions
9.7.2 A Project Example-Wireless Application
References
Appendix A Some Useful Formulas
A.1 Trigonometric Identities
A.2 Geometric Series
A.3 Complex Varables
A.4 Impulse Functions
A.5 Vector Concepts
A.6 Units of Power
Reference
Appendix B Introduction of MATLAB for DSP Applications
B.1 Elementary Operations
B.1.1 Initializing Variables and Vectors
B.1.2 Graphics
B.1.3 Basic Operators
B.1.4 Files
B.2 Genration and Processing of Digital Signals
B.3 DSP Applications
B.4 User-Written Functions
B.5 Summary of Useful MATLAB Functions
References
Appendix C Introduction of C Programming of DSP Applications
C.1 A Simple C Program
C.1.1 Variables and Assignment Operators
C.1.2 Numeric Data Types and Conversion
C.1.3 Arrays
C.2 Arithmetic and Bitwise Operators
C.2.1 Arithmetic Operators
C.2.2 Bitwise Operators
C.3 An FIR Filter Program
C.3.1 Command-Line Arguments
C.3.2 Pointers
C.3.3 C Functions
C.3.4 Files and I/O Operations
C.4 Control Structures and Loops
C.4.1 Control Structures
C.4.2 Logical Operators
C.4.3 Loops
C.5Data Types Used by the TMS320C55x
Appendix D About the Software
Index