自適應信號處理（英文版）簡(jiǎn)介，目錄書(shū)摘
2020-02-17 14:33
來(lái)源：京東
作者：京東
自適應信號處理（英文版）
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內容簡(jiǎn)介: 《自適應信號處理（英文版）》是自適應信號處理方面的一部經(jīng)典著(zhù)作，系統介紹了自適應信號處理的原理、算法和結構及其在各個(gè)領(lǐng)域的應用?！蹲赃m應信號處理（英文版）》既有理論分析，又有物理概念闡述，核心內容是自適應線(xiàn)性組合器、LMS算法、自適應模擬與系統辨識、自適應控制系統、自適應波束形成器的分析?！蹲赃m應信號處理（英文版）》要求讀者具備工程和數學(xué)方面的基礎知識，并具有編寫(xiě)和運行計算機程序的能力。<br> 《自適應信號處理（英文版）》特色：<br> ·從特定工程系統的特性或特征引入自適應的概念；<br> ·描述一種可用于分析所有自適應系統的幾何“性能表面”；<br> ·包含性能表面梯度估值的統計分析，以及各種搜索方法的比較；<br> ·介紹了LMS算法與線(xiàn)性組合器以及其他自適應算法和結構，如序貫回歸算法與自適應格型濾波結構等；<br> ·涵蓋了自適應信號處理的主要應用；<br> ·介紹了自適應模擬與自適應逆模擬，及其在通信和控制領(lǐng)域的應用；<br> ·包含了自適應干擾對消；<br> ·介紹了自適應陣和波束形成。
作者簡(jiǎn)介: 作者：(美國)斯坦福大學(xué) (美國)新墨西哥大學(xué)
目錄:LIST OF SYMBOLS<br>part ⅠGENERAL INTRODUCTION Objectives of Part Ⅰ<br>1 ADAPTIVE SYSTEMS<br>Definition. and Characteristics<br>Areas of Application<br>General Properties<br>Open- and Closed-Loop Adaptation<br>Applications of Closed-Loop Adaptation<br>Example of an Adaptive System<br>The Chapters Ahead<br><br>2 THE ADAPTIVE LINEAR COMBINER<br>General Description<br>Input Signal and Weight Vectors<br>Desired Response and Error<br>The Performance Function<br>Gradient and Minimum Mean-Square Error<br>Example of a Performance Surface<br>Alternative Expression of the GradiEnt<br>Decorrelation of Error and Input Components<br>Exercises<br><br>part Ⅱ THEORY OF ADAPTATION WITH STATIONARY SIGNALS<br>Objectives of Part Ⅱ<br>3 PROPERTIES OF THE QUADRATIC PERFORMANCE SURFACE<br>Normal Form of the Input Correlation Matrix<br>Eigenvalues and Eigenvectors of the Input Correlation Matrix<br>An Example with Two Weights<br>Geometrical Significance of Eigenvectors and Eigenvalues<br>A Second Example<br>Exercises<br><br>4 SEARCHING THE PERFORMANCE SURFACE<br>Methods of Searching the Performance Surface<br>Basic Ideas of Gradient Search Methods<br>A Simple Gradient Search Algorithm and Its Solution<br>Stability and Rate of Convergence<br>The Learning Curve<br>Gradient Search by Newton's Method<br>Newton's Method in Multidimensional Space<br>Gradient Search by the Method of Steepest Descent<br>Comparison of Learning Curves<br>Exercises<br><br>5 GRADIENT ESTIMATION AND ITS EFFECTS ON ADAPTATION<br>Gradient Component Estimation by Derivative Measurement<br>part Ⅲ ADAPTIVE AL GORITHMS AND STRUCTURES<br>part Ⅳ APPLICATIONS<br>APPENDIX A A Portable Random Number Generator<br>INDEX
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