信号、系统及推理（英文版）
| 作者 |
| （美）Alan V. Oppenheim(艾伦 V. 奥本海姆), George C. Verghese（乔治 C. 维盖瑟） |
| 丛书名 |
| 国外电子与通信教材系列 |
| 出版社 |
| 电子工业出版社 |
| ISBN |
| 9787121391682 |
| 简要 |
| 简介 |
| 内容简介书籍通信书籍 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，最小均方误差估计下的最佳线性滤波器，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。 |
| 目录 |
Prologue 开场白\t23 第1章Signals and Systems 信号与系统\t31 1．1Signals， Systems， Models， and Properties 信号、系统、模型及性质\t31 1．1．1System Properties 系统的性质\t33 1．2Linear，Time-Invariant Systems 线性时不变系统\t35 1．2．1Impulse-Response Representation of LTI Systems LTI系统的冲激响应表示\t35 1．2．2Eigenfunction and Transform Representation of LTI Systems LTI系统的特征函数和变换表示\t36 1．2．3Fourier Transforms 傅里叶变换\t40 1．3Deterministic Signals and Their Fourier Transforms 确定性信号及其傅里叶变换\t41 1．3．1Signal Classes and Their Fourier Transforms 信号种类及其傅里叶变换\t41 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\t44 1．4Bilateral Laplace and z-Transforms 双边z变换和双边拉普拉斯变换\t46 1．4．1The Bilateral z-Transform 双边z变换\t46 1．4．2The Bilateral Laplace Transform 双边拉普拉斯变换\t50 1．5Discrete-Time Processing of Continuous-Time Signals 连续时间信号的离散时间处理\t51 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\t52 1．5．2DT Filtering and Overall CT Response 离散时间滤波以及全局连续时间响应\t54 1．5．3Nonideal D/C Converters 非理想的D/C转换器\t56 1．6Further Reading 延伸阅读\t58 Problems 习题\t59 第2章Amplitude， Phase， and Group Delay 幅度、相位和群延迟\t92 2．1Fourier Transform Magnitude and Phase 傅里叶变换的幅度和相位\t92 2．2Group Delay and the Effect of Nonlinear Phase 群延迟和非线性相位的影响\t96 2．2．1Narrowband Input Signals 窄带输入信号\t96 2．2．2Broadband Input Signals 宽带输入信号\t98 2．3All-Pass and Minimum-Phase Systems 全通系统与最小相位系统\t103 2．3．1All-Pass Systems 全通系统\t103 2．3．2Minimum-Phase Systems 最小相位系统\t105 2．4Spectral Factorization 谱因式分解\t108 2．5Further Reading 延伸阅读\t110 Problems 习题\t110 第3章Pulse Amplitude Modulation 脉冲幅度调制\t132 3．1Baseband Pulse Amplitude Modulation 基带脉冲幅度调制\t133 3．1．1The Transmitted Signal 发送信号\t133 3．1．2The Received Signal 接收信号\t135 3．1．3Frequency-Domain Characterizations 频域特性\t135 3．1．4Intersymbol Interference at the Receiver 接收机处的码间干扰\t138 3．2Nyquist Pulses 奈奎斯特脉冲\t140 3．3Passband Pulse Amplitude Modulation 通带脉冲幅度调制\t143 3．3．1Frequency-Shift Keying (FSK) 频移键控\t144 3．3．2Phase-Shift Keying (PSK) 相移键控\t144 3．3．3Quadrature Amplitude Modulation (QAM) 正交幅度调制\t146 3．4Further Reading 延伸阅读\t148 Problems 习题\t149 第4章State-Space Models 状态空间模型\t163 4．1System Memory 系统记忆性\t163 4．2Illustrative Examples 举例说明\t164 4．3State-Space Models 状态空间模型\t176 4．3．1DT State-Space Models 离散时间状态空间模型\t176 4．3．2CT State-Space Models 连续时间状态空间模型\t179 4．3．3Defining Properties of State-Space Models 状态空间模型的典型性质\t181 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\t183 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\t188 4．5．1Equilibrium 平衡状态\t188 4．5．2Linearization 线性化\t191 4．6Further Reading 延伸阅读\t194 Problems 习题\t195 第5章LTI State-Space Models LTI状态空间模型\t204 5．1Continuous-Time and Discrete-Time LTI Models 连续时间和离散时间LTI模型\t204 5．2Zero-Input Response and Modal Representation 零输入响应和模态表示\t207 5．2．1Undriven CT Systems 未驱动的连续时间系统\t207 5．2．2Undriven DT Systems 未驱动的离散时间系统\t215 5．2．3Asymptotic Stability of LTI Systems LTI系统的渐进稳定性\t217 5．3General Response in Modal Coordinates 模态坐标下的通用响应\t221 5．3．1Driven CT Systems 被驱动的连续时间系统\t221 5．3．2Driven DT Systems 被驱动的离散时间系统\t224 5．3．3Similarity Transformations and Diagonalization 相似变换和对角化\t226 5．4Transfer Functions， Hidden Modes， Reachability， and Observability 传输函数、隐藏模式、可达性和可观测性\t232 5．4．1Input-State-Output Structure of CT Systems 连续时间系统的输入状态输出结构\t232 5．4．2Input-State-Output Structure of DT Systems 离散时间系统的输入状态输出结构\t240 5．5Further Reading 延伸阅读\t249 Problems 习题\t250 第6章State Observers and State Feedback 状态观测器和状态反馈\t266 6．1Plant and Model 设备和模型\t267 6．2State Estimation and Observers 状态估计和观测器\t269 6．2．1Real-Time Simulation 实时仿真\t269 6．2．2The State Observer 状态观测器\t271 6．2．3Observer Design 观测器设计\t273 6．3State Feedback Control 状态反馈控制\t282 6．3．1Open-Loop Control 开环控制\t282 6．3．2Closed-Loop Control via LTI State Feedback 经由LTI状态反馈的闭环控制\t283 6．3．3LTI State Feedback Design LTI状态反馈设计\t284 6．4Observer-Based Feedback Control 基于观测器的反馈控制\t292 6．5Further Reading 延伸阅读\t297 Problems 习题\t297 第7章Probabilistic Models 概率模型\t309 7．1The Basic Probability Model 基本概率模型\t309 7．2Conditional Probability， Bayes’ Rule， and Independence 条件概率、贝叶斯法则和事件的独立性\t310 7．3Random Variables 随机变量\t313 7．4Probability Distributions 概率分布\t313 7．5Jointly Distributed Random Variables 联合分布的随机变量\t315 7．6Expectations， Moments， and Variance 期望、矩和方差\t317 7．7Correlation and Covariance for Bivariate Random Variables 二元随机变量的相关性和协方差\t320 7．8A Vector-Space Interpretation of Correlation Properties 向量空间中的相关性质\t324 7．9Further Reading 延伸阅读\t326 Problems 习题\t327 第8章Estimation 估计算法\t336 8．1Estimation of a Continuous Random Variable 单个连续随机变量的估计\t337 8．2From Estimates to the Estimator 从估计到估计器\t342 8．2．1Orthogonality 正交性\t347 8．3Linear Minimum Mean Square Error Estimation 线性最小均方误差估计\t348 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\t348 8．3．2Multiple Measurements 多重量测\t353 8．4Further Reading 延伸阅读\t357 Problems 习题\t358 第9章Hypothesis Testing 假设检验\t373 9．1Binary Pulse-Amplitude Modulation in Noise 噪声中的二进制脉冲幅度调制\t373 9．2Hypothesis Testing with Minimum Error Probability 最小差错概率下的假设检验\t375 9．2．1Deciding with Minimum Conditional Probability of Error 最小条件差错概率的判决\t376 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\t377 9．2．3Hypothesis Testing in Coded Digital Communication 编码数字通信中的假设检验\t380 9．3Binary Hypothesis Testing 二元假设检验\t383 9．3．1False Alarm， Miss， and Detection 虚警、漏警和检测\t384 9．3．2The Likelihood Ratio Test 似然比检验\t386 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\t387 9．4Minimum Risk Decisions 最小风险判决\t391 9．5Further Reading 延伸阅读\t393 Problems 习题\t393 第10章Random Processes 随机过程\t410 10．1Definition and Examples of a Random Process 随机过程的定义和举例\t410 10．2First-and Second-Moment Characterization of Random Processes 随机过程的一阶矩和二阶矩特性\t415 10．3Stationarity 平稳性\t416 10．3．1Strict-Sense Stationarity 严格平稳性\t416 10．3．2Wide-Sense Stationarity 广义平稳性\t416 10．3．3Some Properties of WSS Correlation and Covariance Functions WSS相关函数和协方差函数的性质\t418 10．4Ergodicity 各态历经性\t421 10．5Linear Estimation of Random Processes 随机过程的线性估计\t422 10．5．1Linear Prediction 线性预测\t422 10．5．2Linear FIR Filtering 线性FIR滤波\t424 10．6LTI Filtering of WSS Processes WSS过程的LTI滤波\t425 10．7Further Reading 延伸阅读\t431 Problems 习题\t431 第11章Power Spectral Density 功率谱密度\t451 11．1Spectral Distribution of Expected Instantaneous Power 瞬时功率期望的频谱分布\t452 11．1．1Power Spectral Density 功率谱密度\t452 11．1．2Fluctuation Spectral Density 波动谱密度\t456 11．1．3Cross-Spectral Density 互谱密度\t461 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\t462 11．3Applications 应用\t467 11．3．1Revealing Cyclic Components 揭示循环分量\t467 11．3．2Modeling Filters 模型滤波器\t469 11．3．3Whitening Filters 白化滤波器\t473 11．3．4Sampling Bandlimited Random Processes 带限随机过程的采样\t474 11．4Further Reading 延伸阅读\t474 Problems 习题\t475 第12章Signal Estimation 信号估计\t494 12．1LMMSE Estimation for Random Variables 随机变量的LMMSE估计\t495 12．2FIR Wiener Filters FIR维纳滤波器\t497 12．3The Unconstrained DT Wiener Filter 无约束的离散时间维纳滤波器\t502 12．4Causal DT Wiener Filtering 离散时间的因果维纳滤波\t510 12．5Optimal Observers and Kalman Filtering 最佳观测器和卡尔曼滤波\t517 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\t517 12．5．2Observer Implementation of the Wiener Filter 维纳滤波器的观测器实现\t519 12．5．3Optimal State Estimates and Kalman Filtering 最佳状态估计和卡尔曼滤波\t521 12．6Estimation of CT Signals 连续时间信号的估计\t522 12．7Further Reading 延伸阅读\t523 Problems 习题\t523 第13章Signal Detection 信号检测\t541 13．1Hypothesis Testing with Multiple Measurements 基于多重量测的假设检验\t542 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\t544 13．2．1The Optimal Solution 最佳检测方案\t545 13．2．2Characterizing Performance 性能描述\t547 13．2．3Matched Filtering 匹配滤波\t549 13．3Extensions of Matched-Filter Detection 匹配滤波器检测的推广\t552 13．3．1Infinite-Duration， Finite-Energy Signals 无限长度的有限能量信号\t552 13．3．2Maximizing SNR for Signal Detection in White Noise 白噪声中信号检测的SNR最大化\t552 13．3．3Detection in Colored Noise 有色噪声中的检测\t555 13．3．4Continuous-Time Matched Filters 连续时间匹配滤波器\t558 13．3．5Matched Filtering and Nyquist Pulse Design 匹配滤波和奈奎斯特脉冲设计\t559 13．3．6Unknown Arrival Time and Pulse Compression 未知的到达时间和脉冲压缩\t560 13．4Signal Discrimination in I．I．D． Gaussian Noise 独立同分布高斯噪声中的信号识别\t562 13．5Further Reading 延伸阅读\t568 Problems 习题\t568 Bibliography 参考文献\t585 Index 索引 |
有问题微信扫码联系