信号、系统及推理(英文版)-图书推荐

目录

Prologue
开场白23
章Signals and Systems
信号与系统31
1.1Signals, Systems, Models, and Properties
信号、系统、模型及性质31
1.1.1System Properties
系统的性质33
1.2Linear,Time-Invariant Systems
线性时不变系统35
1.2.1Impulse-Response Representation of LTI Systems
LTI系统的冲激响应表示35
1.2.2Eigenfunction and Transform Representation of LTI Systems
LTI系统的特征函数和变换表示36
1.2.3Fourier Transforms
傅里叶变换40
1.3Deterministic Signals and Their Fourier Transforms
确定性信号及其傅里叶变换41
1.3.1Signal Classes and Their Fourier Transforms
信号种类及其傅里叶变换41
1.3.2Parseval’s Identity, Energy Spectral Density, and Deterministic Autocorrelation
Parseval恒等式、能量谱密度以及确定性自相关44
1.4Bilateral Laplace and z-Transforms
双边z变换和双边拉普拉斯变换46
1.4.1The Bilateral z-Transform
双边z变换46
1.4.2The Bilateral Laplace Transform
双边拉普拉斯变换50
1.5Discrete-Time Processing of Continuous-Time Signals
连续时间信号的离散时间处理51
1.5.1Basic Structure for DT Processing of CT Signals
连续时间信号的离散时间处理过程的基本结构52
1.5.2DT Filtering and Overall CT Response
离散时间滤波以及全局连续时间响应54
1.5.3Nonideal D/C Converters
非理想的D/C转换器56
1.6Further Reading
延伸阅读58
Problems
习题59
第2章Amplitude, Phase, and Group Delay
幅度、相位和群延迟92
2.1Fourier Transform Magnitude and Phase
傅里叶变换的幅度和相位92
2.2Group Delay and the Effect of Nonlinear Phase
群延迟和非线性相位的影响96
2.2.1Narrowband Input Signals
窄带输入信号96
2.2.2Broadband Input Signals
宽带输入信号98
2.3All-Pass and Minimum-Phase Systems
全通系统与最小相位系统103
2.3.1All-Pass Systems
全通系统103
2.3.2Minimum-Phase Systems
最小相位系统105
2.4Spectral Factorization
谱因式分解108
2.5Further Reading
延伸阅读110
Problems
习题110
第3章Pulse Amplitude Modulation
脉冲幅度调制132
3.1Baseband Pulse Amplitude Modulation
基带脉冲幅度调制133
3.1.1The Transmitted Signal
发送信号133
3.1.2The Received Signal
接收信号135
3.1.3Frequency-Domain Characterizations
频域特性135
3.1.4Intersymbol Interference at the Receiver
接收机处的码间干扰138
3.2Nyquist Pulses
奈奎斯特脉冲140
3.3Passband Pulse Amplitude Modulation
通带脉冲幅度调制143
3.3.1Frequency-Shift Keying (FSK)
频移键控144
3.3.2Phase-Shift Keying (PSK)
相移键控144
3.3.3Quadrature Amplitude Modulation (QAM)
正交幅度调制146
3.4Further Reading
延伸阅读148
Problems
习题149
第4章State-Space Models
状态空间模型163
4.1System Memory
系统记忆性163
4.2Illustrative Examples
举例说明164
4.3State-Space Models
状态空间模型176
4.3.1DT State-Space Models
离散时间状态空间模型176
4.3.2CT State-Space Models
连续时间状态空间模型179
4.3.3Defining Properties of State-Space Models
状态空间模型的典型性质181
4.4State-Space Models from LTI Input-Output Models
基于LTI输入输出模型的状态空间模型183
4.5Equilibria and Linearization of Nonlinear State-Space Models
非线性状态空间模型的平衡状态和线性化188
4.5.1Equilibrium
平衡状态188
4.5.2Linearization
线性化191
4.6Further Reading
延伸阅读194
Problems
习题195
第5章LTI State-Space Models
LTI状态空间模型204
5.1Continuous-Time and Discrete-Time LTI Models
连续时间和离散时间LTI模型204
5.2Zero-Input Response and Modal Representation
零输入响应和模态表示207
5.2.1Undriven CT Systems
未驱动的连续时间系统207
5.2.2Undriven DT Systems
未驱动的离散时间系统215
5.2.3Asymptotic Stability of LTI Systems
LTI系统的渐进稳定性217
5.3General Response in Modal Coordinates
模态坐标下的通用响应221
5.3.1Driven CT Systems
被驱动的连续时间系统221
5.3.2Driven DT Systems
被驱动的离散时间系统224
5.3.3Similarity Transformations and Diagonalization
相似变换和对角化226
5.4Transfer Functions, Hidden Modes, Reachability, and Observability
传输函数、隐藏模式、可达性和可观测性232
5.4.1Input-State-Output Structure of CT Systems
连续时间系统的输入状态输出结构232
5.4.2Input-State-Output Structure of DT Systems
离散时间系统的输入状态输出结构240
5.5Further Reading
延伸阅读249
Problems
习题250
第6章State Observers and State Feedback
状态观测器和状态反馈266
6.1Plant and Model
设备和模型267
6.2State Estimation and Observers
状态估计和观测器269
6.2.1Real-Time Simulation
实时仿真269
6.2.2The State Observer
状态观测器271
6.2.3Observer Design
观测器设计273
6.3State Feedback Control
状态反馈控制282
6.3.1Open-Loop Control
开环控制282
6.3.2Closed-Loop Control via LTI State Feedback
经由LTI状态反馈的闭环控制283
6.3.3LTI State Feedback Design
LTI状态反馈设计284
6.4Observer-Based Feedback Control
基于观测器的反馈控制292
6.5Further Reading
延伸阅读297
Problems
习题297
第7章Probabilistic Models
概率模型309
7.1The Basic Probability Model
基本概率模型309
7.2Conditional Probability, Bayes’ Rule, and Independence
条件概率、贝叶斯法则和事件的独立性310
7.3Random Variables
随机变量313
7.4Probability Distributions
概率分布313
7.5Jointly Distributed Random Variables
联合分布的随机变量315
7.6Expectations, Moments, and Variance
期望、矩和方差317
7.7Correlation and Covariance for Bivariate Random Variables
二元随机变量的相关性和协方差320
7.8A Vector-Space Interpretation of Correlation Properties
向量空间中的相关性质324
7.9Further Reading
延伸阅读326
Problems
习题327
第8章Estimation
估计算法336
8.1Estimation of a Continuous Random Variable
单个连续随机变量的估计337
8.2From Estimates to the Estimator
从估计到估计器342
8.2.1Orthogonality
正交性347
8.3Linear Minimum Mean Square Error Estimation
线性最小均方误差估计348
8.3.1Linear Estimation of One Random Variable from a Single Measurement of Another
从一个随机变量的单次量测中线性估计另一个随机变量348
8.3.2Multiple Measurements
多重量测353
8.4Further Reading
延伸阅读357
Problems
习题358
第9章Hypothesis Testing
假设检验373
9.1Binary Pulse-Amplitude Modulation in Noise
噪声中的二进制脉冲幅度调制373
9.2Hypothesis Testing with Minimum Error Probability
最小差错概率下的假设检验375
9.2.1Deciding with Minimum Conditional Probability of Error
最小条件差错概率的判决376
9.2.2MAP Decision Rule for Minimum Overall Probability of Error
最小化总体差错概率的MAP判决准则377
9.2.3Hypothesis Testing in Coded Digital Communication
编码数字通信中的假设检验380
9.3Binary Hypothesis Testing
二元假设检验383
9.3.1False Alarm, Miss, and Detection
虚警、漏警和检测384
9.3.2The Likelihood Ratio Test
似然比检验386
9.3.3Neyman-Pearson Decision Rule and Receiver Operating Characteristic
纽曼-皮尔逊判决准则和接收者操作特性387
9.4Minimum Risk Decisions
最小风险判决391
9.5Further Reading
延伸阅读393
Problems
习题393
0章Random Processes
随机过程410
10.1Definition and Examples of a Random Process
随机过程的定义和举例410
10.2First-and Second-Moment Characterization of Random Processes
随机过程的一阶矩和二阶矩特性415
10.3Stationarity
平稳性416
10.3.1Strict-Sense Stationarity
严格平稳性416
10.3.2Wide-Sense Stationarity
广义平稳性416
10.3.3Some Properties of WSS Correlation and Covariance Functions
WSS相关函数和协方差函数的性质418
10.4Ergodicity
各态历经性421
10.5Linear Estimation of Random Processes
随机过程的线性估计422
10.5.1Linear Prediction
线性预测422
10.5.2Linear FIR Filtering
线性FIR滤波424
10.6LTI Filtering of WSS Processes
WSS过程的LTI滤波425
10.7Further Reading
延伸阅读431
Problems
习题431
1章Power Spectral Density
功率谱密度451
11.1Spectral Distribution of Expected Instantaneous Power
瞬时功率期望的频谱分布452
11.1.1Power Spectral Density
功率谱密度452
11.1.2Fluctuation Spectral Density
波动谱密度456
11.1.3Cross-Spectral Density
互谱密度461
11.2Expected Time-Averaged Power Spectrum and the Einstein-Wiener-Khinchin Theorem
时间平均的功率谱期望和爱因斯坦-维纳-辛钦理论462
11.3Applications
应用467
11.3.1Revealing Cyclic Components
揭示循环分量467
11.3.2Modeling Filters
模型滤波器469
11.3.3Whitening Filters
白化滤波器473
11.3.4Sampling Bandlimited Random Processes
带限随机过程的采样474
11.4Further Reading
延伸阅读474
Problems
习题475
2章Signal Estimation
信号估计494
12.1LMMSE Estimation for Random Variables
随机变量的LMMSE估计495
12.2FIR Wiener Filters
FIR维纳滤波器497
12.3The Unconstrained DT Wiener Filter
无约束的离散时间维纳滤波器502
12.4Causal DT Wiener Filtering
离散时间的因果维纳滤波510
12.5Optimal Observers and Kalman Filtering
最佳观测器和卡尔曼滤波517
12.5.1Causal Wiener Filtering of a Signal Corrupted by Additive Noise
受加性噪声干扰的信号的因果维纳滤波517
12.5.2Observer Implementation of the Wiener Filter
维纳滤波器的观测器实现519
12.5.3Optimal State Estimates and Kalman Filtering
最佳状态估计和卡尔曼滤波521
12.6Estimation of CT Signals
连续时间信号的估计522
12.7Further Reading
延伸阅读523
Problems
习题523
3章Signal Detection
信号检测541
13.1Hypothesis Testing with Multiple Measurements
基于多重量测的假设检验542
13.2Detecting a Known Signal in I.I.D. Gaussian Noise
独立同分布高斯噪声中已知信号的检测544
13.2.1The Optimal Solution
最佳检测方案545
13.2.2Characterizing Performance
性能描述547
13.2.3Matched Filtering
匹配滤波549
13.3Extensions of Matched-Filter Detection
匹配滤波器检测的推广552
13.3.1Infinite-Duration, Finite-Energy Signals
无限长度的有限能量信号552
13.3.2Maximizing SNR for Signal Detection in White Noise
白噪声中信号检测的SNR优选化552
13.3.3Detection in Colored Noise
有色噪声中的检测555
13.3.4Continuous-Time Matched Filters
连续时间匹配滤波器558
13.3.5Matched Filtering and Nyquist Pulse Design
匹配滤波和奈奎斯特脉冲设计559
13.3.6Unknown Arrival Time and Pulse Compression
未知的到达时间和脉冲压缩560
13.4Signal Discrimination in I.I.D. Gaussian Noise
独立同分布高斯噪声中的信号识别562
13.5Further Reading
延伸阅读568
Problems
习题568
Bibliography
参考文献585
Index
索引

主编推荐

"奥本海姆近年力作; 本书立足的由基本原理和概念所构架的信号、系统、概率的研究和应用很好丰富,支持的领域很好广泛,有着丰富的历史重要性,因此内容很好丰富; 本书将信号与系统状态、模态结合起来,将观测器与滤波理论结合起来,无论是在状态估计还是信号检测上,构成的推理具有数学上的基础和普适性的应用; 本书在信号与系统的基础上,融合并扩展了信号与系统时频域分析的基本素材和概率论知识; 书中所提出的“推理”(Inference)是结合先验知识和可用的信号量测来归纳不确定性的存在性的,从而领引信号与系统后续课程的建设。"

内容简介

本书是美国麻省理工学院(MIT)知名教授奥本海姆的近年力作,是其在MIT开展了二十余年的Signals,Systems and Inference课程所涉及知识体系的拓展和延伸。本书详细阐述了确定性信号与系统的性质和表示形式,包括群延迟和状态空间模型的结构与行为;引入了相关函数和功率谱密度来描述和处理随机信号。本书涉及的应用实例包括脉冲幅度调制,基于观测器的反馈控制,很小均方误差估计下的很好线性滤波器,以及匹配滤波器;强调了基于模型的推理方法,特别是针对状态估计、信号估计和信号检测的应用。本书融合并扩展了信号与系统时频域分析的基本素材和概率论知识,这些都是信号处理、控制、通信、金融工程、生物医学工程等工程和应用科学领域的基本分析方法。

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