书籍详情
实时数字信号处理
作者：郭（Kuo,S.M.），李（Lee,B.h.） 著
出版社：清华大学出版社
出版时间：2003-12-01
ISBN：9787302077008
定价：¥49.80
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内容简介
“实时”功能是高性能数字信号处理器和DSP应用中面临的最新挑战。它的成功应用不仅需要彻底理解DSP理论，还要全面掌握实时DSP设计和应用技术。本书为读者提供了一本非常实用的教材和参考书。本书具有如下特点：具有使用MATLAB，C和TMS320C55X汇编语言的丰富的习题和实验，涵盖了从基本概念到通信应用的所有内容。对数字信号处理的理论问题的讨论，没有复杂的理论推导，而且都是围绕如何实现来展开的。指导如何选择DSP芯片使之满足各种不同应用的要求，如实时性约束、不同硬件选择、定点或浮点器件等。[前言]本书的中文名字可以译为《实时数字信号处理：基于TMS320C55X的实现、应用和实验》。所谓"实时（Real-Time）实现"，是指一个实际的系统在人们听觉、视觉或按任务要求所允许的时间范围内能及时地完成对输入信号的处理并将其输出。例如，我们每天使用的手机、将要普及的数字电视等，都是实时的数字信号处理系统。要想在极短的时间内完成对信号的处理，一方面需要快速的算法、高效的编程，另一方面，则需要高性能的硬件支持。数字信号处理器（DSP）即是为实时实现数字信号处理任务而特殊设计的高性能的一类CPU。随着信息科学和微电子技术的飞速发展，数字信号处理的理论及数字信号处理器已广泛应用于通信、家电、航空航天、工业测量和控制、生物医学工程及军事等许许多多的领域。由于设计和实现一个实时的数字信号处理系统不仅需要系统地掌握信号处理的理论，而且要熟练地掌握DSP硬件的知识，因此，对设计者的要求是非常高、也是相当全面的。美国伊利诺斯大学电机工程系的SenM.Kuo教授和美国德州仪器公司的BobH.Lee博士合著的这本书为培养这一类人才提供了一本值得推荐的好教材。本书共分9章。第1章简要介绍了实时数字信号处理系统的基本概念；第2章介绍了美国德州仪器公司最新推出的DSP芯片：TMS320C55X的结构及编程；第3章讨论了DSP系统实时实现时的结构、量化及溢出等问题；第4～8章分别讨论数字信号处理中的时域分析、频域分析、FIR和IIR滤波器设计、快速傅里叶交换及自适应滤波等基本问题；第9章较为详细地给出了DSP实时系统应用的例子，如信号产生（正弦信号、Chirp信号、噪声等），自适应噪声抵消及语音增强等。本书的特点是：1.全书以TMS320C55XDSP芯片为主线，系统地介绍了实时数字信号处理系统的设计和实现问题。2.本书虽然也以较大的篇幅讨论了数字信号处理的理论问题，但目的都是围绕着如何实现来展开的。3.本书每一章都安排了实验举例，或用C55的汇编语言，或用C语言来说明该章内容在DSP上的实现问题。通过这些实验，读者可以很快地掌握实时DSP系统的设计和实现问题。4.除第9章，本书每一章都附有丰富的习题。这些习题一部分是涉及信号处理的理论问题，但大部分是有关实时DSP系统实现的上机练习。5.本书没有涉及复杂的理论推导，因此通俗易懂。本书可作为本科生、研究生的教材，也可作为工程技术人员的参考书。
作者简介
暂缺《实时数字信号处理》作者简介
目录
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
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
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