内容简介
《信号与系统(第二版 英文版)》是美国麻省理工学院(MIT)的经典教材之一,讨论了信号与系统分析的基本理论、基本分析方法及其应用。全书共分11章,主要讲述了线性系统的基本理论、信号与系统的基本概念、线性时不变系统、连续与离散信号的傅里叶表示、傅里叶变换以及时域和频域系统的分析方法等内容。《信号与系统(第二版 英文版)》作者使用了大量在滤波、采样、通信和反馈系统中的实例,并行讨论了连续系统、离散系统、时域系统和频域系统的分析方法,使读者能透彻地理解各种信号系统的分析方法并比较其异同。
目录
CONTENTS
1 SIGNALS AND SYSTEMS 1
1.0 Introduction 1
1.1 Continuous-Time and Discrete-Time Signals 1
1.1.1 Examples and Mathematical Representation 1
1.1.2 Signal Energy and Power 5
1.2 Transformations of the Independent Variable 7
1.2.1 Examples of Transformations of the Independent Variable 8
1.2.2 Periodic Signals 11
1.2.3 Even and Odd Signals 13
1.3 Exponential and Sinusoidal Signals 14
1.3.1 Continuous-Time Complex Exponential and Sinusoidal Signals 15
1.3.2 Discrete-Time Complex Exponential and Sinusoidal Signals 21
1.3.3 Periodicity Properties of Discrete-Time Complex Exponentials 25
1.4 The Unit Impulse and Unit Step Functions 30
1.4.1 The Discrete-Time Unit Impulse and Unit Step Sequences 30
1.4.2 The Continuous-Time Unit Step and Unit Impulse Functions 32
1.5 Continuous-Time and Discrete-Time Systems 38
1.5.1 Simple Examples of Systems 39
1.5.2 Interconnections of Systems 41
1.6 Basic System Properties 44
1.6.1 Systems with and without Memory 44
1.6.2 Invertibility and Inverse Systems 45
1.6.3 Causality 46
1.6.4 Stability 48
1.6.5 Time Invariance 50
1.6.6 Linearity 53
1.7 Summary 56
Problems 57
2 LINEAR TIME-INVARIANT SYSTEMS 74
2.0 Introduction 74
2.1 Discrete-Time LTI Systems: The Convolution Sum 75
2.1.1 The Representation of Discrete-Time Signals in Terms
of Impulses 75
2.1.2 The Discrete-Time Unit Impulse Response and the Convolution-Sum
Representation of LTI Systems 77
2.2 Continuous-Time LTI Systems: The Convolution Integral 90
2.2.1 The Representation of Continuous-Time Signals in Terms
of Impulses 90
2.2.2 The Continuous-Time Unit Impulse Response and the Convolution
Integral Representation of LTI Systems 94
2.3 Properties of Linear Time-invariant Systems 103
2.3.1 The Commutative Property 104
2.3.2 The Distributive Property 104
2.3.3 The Associative Property 107
2.3.4 LTI Systems with and without Memory 108
2.3.5 Invertibility of LTI Systems 109
2.3.6 Causality for LTI Systems 112
2.3.7 Stability for LTI Systems 113
2.3.8 The Unit Step Response of an LTI System 115
2.4 Causal LTI Systems Described by Differential and Difference
Equations 116
2.4.1 Linear Constant-Coefficient Differential Equations 117
2.4.2 Linear Constant-Coefficient Difference Equations 121
2.4.3 Block Diagram Representations of First-Order Systems Described
by Differential and Difference Equations 124
2.5 Singularity Functions 127
2.5.1 The Unit Impulse as an Idealized Short Pulse 128
2.5.2 Defining the Unit Impulse through Convolution 131
2.5.3 Unit Doublets and Other Singularity Functions 132
2.6 Summary 137
Problems 137
3 FOURIER SERIES REPRESENTATION OF PERIODIC SIGNALS 177
3.0 Introduction 177
3.1 A Historical Perspective 178
3.2 The Response of LTI Systems to Complex Exponentials 182
3.3 Fourier Series Representation of Continuous-Time
Periodic Signals 186
3.3.1 Linear Combinations of Harmonically Related Complex
Exponentials 186
3.3.2 Determination of the Fourier Series Representation
of a Continuous-Time Periodic Signal 190
3.4 Convergence of the Fourier Series 195
3.5 Properties of Continuous-Time Fourier Series 202
3.5.1 Linearity 202
3.5.2 Time Shifting 202
3.5.3 Time Reversal 203
3.5.4 Time Scaling 204
3.5.5 Multiplication 204
3.5.6 Conjugation and Conjugate Symmetry 204
3.5.7 Parseval's Relation for Continuous-Time Periodic Signals 205
3.5.8 Summary of Properties of the Continuous-Time Fourier Series 205
3.5.9 Examples 205
3.6 Fourier Series Representation of Discrete-Time
Periodic Signals 211
3.6.1 Linear Combinations of Harmonically Related Complex
Exponentials 211
3.6.2 Determination of the Fourier Series Representation of a
Periodic Signal 212
3.7 Properties of Discrete-Time Fourier Series 221
3.7.1 Multiplication 222
3.7.2 First Difference 222
3.7.3 Parseval's Relation for Discrete-Time Periodic Signals 223
3.7.4 Examples 223
3.8 Fourier Series and LTI Systems 226
3.9 Filtering 231
3.9.1 Frequency-Shaping Filters 232
3.9.2 Frequency-Selective Filters 236
3.10 Examples of Continuous-Time Filters Described by
Differential Equations 239
3.10.1 A Simple RC Lowpass Filter 239
3.10.2 A Simple RC Highpass Filter 241
3.11 Examples of Discrete-Time Filters Described by
Difference Equations 244
3.11.1 First-Order Recursive Discrete-Time Filters 244
3.11.2 Nonrecursive Discrete-Time Filters 245
3.12 Summary 249
Problems 250
4 THE CONTINUOUS-TIME FOURIER TRANSFORM 2,84
4.0 Introduction 284
4.1 Representation of Aperiodic Signals: The Continuous-Time
Fourier Transform 285
4.1.1 Development of the Fourier Transform Representation
of an Aperiodic.Signal 285
4.1.2 Convergence of Fourier Transforms 289
4.1.3 Examples of Continuous-Time Fourier Transforms 290
4.2 The Fourier Transform for Periodic Signals 296
4.3 Properties of the Continuous-Time Fourier Transform 300
4.3.1 Linearity 301
4.3.2 Time Shifting 301
4.3.3 Conjugation and Conjugate Symmetry 303
4.3.4 Differentiation and Integration 306
4.3.5 Time and Frequency Scaling 308
4.3.6 Duality 309
4.3.7 Parseval's Relation 312
4.4 The Convolution Property 314
4.4.1 Examples 317
4.5 The Multiplication Property 322
4.5.1 Frequency-Selective Filtering with Variable Center Frequenc) 325
4.6 Tables of Fourier Properties and of Basic Fourier
Transform Pairs 328
4.7 Systems Characterized by Linear Constant-Coefficient
Differential Equations 330
4.8 Summary 333
Problems 334
5 THE DISCRETE-TIME FOURIER TRANSFORM 358
5.0 Introduction 358
5.1 Representation of Aperiodic Signals: The Discrete-Time
Fourier Transform 359
5.1.1 Development of the Discrete-Time Fourier Transform 359
5.1.2 Examples of Discrete-Time Fourier Transforms 362
5.1.3 Convergence Issues Associated with the Discrete-Time Fourier
Transform 366
5.2 The Fourier Transform for Periodic Signals 367
5.3 Properties of the Discrete-Time Fourier Transform 372
5.3.1 Periodicity of the Discrete-Time Fourier Transform 373
5,3.2 Linearity of the Fourier Transform 373
5.3.3 Time Shifting and Frequency Shifting 373
5.3.4 Conjugation and Conjugate Symmetry 375
5.3.5 Differencing and Accumulation 375
5.3.6 Time Reversal 376
5.3.7 Time Expansion 377
5.3.8 Differentiation in Frequency 380
5.3.9 Parseval's Relation 380
5.4 The Convolution Property 382
5.4.1 Examples 383
5.5 The Multiplication Property 388
5.6 Tables of Fourier Transform Properties and Basic Fourier
Transform Pairs 390
5.7 Duality 390
5.7.1 Duality in the Discrete-Time Fourier Series 391
5.7.2 Duality between the Discrete-Time Fourier Transform ~md the
Continuous-Time Fourier Series 395
5.8 Systems Characterized by Linear Constant-Coefficient
Difference Equations 396
5.9 Summary 399
Problems 400
6 TIME AND FREQUENCY CHARACTERIZATION
OF SIGNALS AND SYSTEMS 423
6.0 Introduction 423
6.1 The Magnitude-Phase Representation of the Fourier
Transform 423
6.2 The Magnitude-Phase Representation of the Frequency Response
of LTI Systems 427
6.2.1 Linear and Nonlinear Phase 428
6.2.2 Group Delay 430
6.2.3 Log-Magnitude and Phase Plots 436
6.3 Time-Domain Properties of Ideal Frequency-Selective
Filters 439
6.4 Time-Domain and Frequency-Domain Aspects of Nonideal
Filters 444
6.5 First-Order and Second-Order Continuous-Time Systems 448
6.5.1 First-Order Continuous-Time Systems 448
6.5.2 Second-Order Continuous-Time Systems 451
6.5.3 Bode Plots for Rational Frequency Responses 456
6.6 First-Order and Second-Order Discrete-Time Systems 461
6.6.1 First-Order Discrete-Time Systems 461
6.6.2 Second-Order Discrete-Time Systems 465
6.7 Examples of Time- and Frequency-Domain Analysis
of Systems 472
6.7.1 Analysis of an Automobile Suspension System 473
6.7.2 Examples of Discrete-Time Nonrecursive Filters 476
6.8 Summary 482
Problems 483
7 SAMPLING 514
7.0 Introduction 514
7.1 Representation of a Continuous-Time Signal by Its Samples:
The Sampling Theorem 515
7.1.1 Impulse-Train Sampling 516
7.1.2 Sampling with a Zero-Order Hold 520
7.2 Reconstruction of a Signal from Its Samples Using
Interpolation 522
7.3 The Effect of Undersampling:
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