Mendeley出力
＜図書＞
Stochastic approximation and its applications
| 責任表示 | by Han-Fu Chen |
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| シリーズ | Nonconvex optimization and its applications ; v. 64 |
| データ種別 | 図書 |
| 出版情報 | Dordrecht : Kluwer Academic , c2002 |
| 本文言語 | 英語 |
| 大きさ | xiii, 357 p. : ill. ; 25 cm |
| 概要 | This book presents the recent development of stochastic approximation algorithms with expanding truncations based on the TS method, a newly developed method for convergence analysis. The general conve...gence theorem is presented for sample paths and is proved in a purely deterministic way, and convergence rates, asymptotic normality, and other asymptotic properties are presented as well. Applications of the developed theory to global optimization, blind channel identification, adaptive filtering, system parameter identification, adaptive stabilization, and other problems from engineering are demonstrated. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com) 続きを見る |
| 目次 | Machine generated contents note: Preface Acknowledgments 1. ROBBINS-MONRO ALGORITHM 1.1 Finding Zeros of a Function. 1.2 Probabilistic Method 1.3 ODE Method 1.4 Truncated RM Algorithm and TS Method 1.5 Weak Convergence Method 1.6 Notes and References 2. STOCHASTIC APPROXIMATION ALGORITHMS WITH EXPANDING TRUNCATIONS 2.1 Motivation 2.2 General Convergence Theorems by TS Method 2.3 Convergence Under State-Independent Conditions 2.4 Necessity of Noise Condition 2.5 Non-Additive Noise 2.6 Connection Between Trajectory Convergence and Proper of Limit Points 2.7 Robustness of Stochastic Approximation Algorithms 2.8 Dynamic Stochastic Approximation 2.9 Notes and References 3. ASYMPTOTIC PROPERTIES OF STOCHASTIC APPROXIMATION ALGORITHMS 3.1 Convergence Rate: Nondegenerate Case 3.2 Convergence Rate: Degenerate Case 3.3 Asymptotic Normality STOCHASTIC APPROXIMATION AND ITS APPLICATIONS 3.4 Asymptotic Efficiency 3.5 Notes and References 4. OPTIMIZATION BY STOCHASTIC APPROXIMATION 4.1 Kiefer-Wolfowitz Algorithm with Randomized Differences 4.2 Asymptotic Properties of KW Algorithm 4.3 Global Optimization 4.4 Asymptotic Behavior of Global Optimization Algorithm 4.5 Application to Model Reduction 4.6 Notes and References 5. APPLICATION TO SIGNAL PROCESSING 5.1 Recursive Blind Identification 5.2 Principal Component Analysis 5.3 Recursive Blind Identification by PCA 5.4 Constrained Adaptive Filtering 5.5 Adaptive Filtering by Sign Algorithms 5.6 Asynchronous Stochastic Approximation 5.7 Notes and References 6. APPLICATION TO SYSTEMS AND CONTROL 6.1 Application to Identification and Adaptive Control 6.2 Application to Adaptive Stabilization 6.3 Application to Pole Assignment for Systems with Unknown Coefficients 6.4 Application to Adaptive Regulation 6.5 Notes and References Appendices A.1 Probability Space A.2 Random Variable and Distribution Function A.3 Expectation A.4 Convergence Theorems and Inequalities A.5 Conditional Expectation A.6 Independence A.7 Ergodicity B.1 Convergence Theorems for Martingale B.2 Convergence Theorems for MDS I B.3 Borel-Cantelli-L6vy Lemma B.4 Convergence Criteria for Adapted Sequences B.5 Convergence Theorems for MDS II B.6 Weighted Sum of MDS References. |
| 電子版へのリンク | https://hdl.handle.net/2324/6973097 |
所蔵情報
| 状態 | 巻次 | 所蔵場所 | 請求記号 | 刷年 | 文庫名称 | 資料番号 | コメント | 予約・取寄 | 複写申込 | 自動書庫 |
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中央図 自動書庫 | 417/C 37/20030157 | 2002 |
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017212003001576 |
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書誌詳細
| 一般注記 | Includes bibliographical references (p. 347-353) and index |
|---|---|
| 著者標目 | *Chen, Han-Fu |
| 書誌ID | 1000936810 |
| ISBN | 1402008066 |
| NCID | BA58896581 |
| 巻冊次 | ISBN:1402008066 |
| 登録日 | 2009.09.16 |
| 更新日 | 2017.02.18 |