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Adaptation and learning in automatic systems /

Adaptation and learning in automatic systems.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: �T�Sypkin, �I�A. Z. (�I�Akov Zalmanovich)
Formato: Electrónico eBook
Idioma:Inglés
Ruso
Publicado: New York : Academic Press, 1971.
Colección:Mathematics in science and engineering ; v. 73.
Temas:
Acceso en línea:Texto completo
Texto completo
Texto completo

MARC

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100 1 |a �T�Sypkin, �I�A. Z.  |q (�I�Akov Zalmanovich) 
240 1 0 |a Adapta�t�si�i�a i obuchenie v avtomaticheskikh sistemakh.  |l English 
245 1 0 |a Adaptation and learning in automatic systems /  |c Ya. Z. Tsypkin ; rranslated by Z.J. Nikolic. 
260 |a New York :  |b Academic Press,  |c 1971. 
300 |a 1 online resource (xix, 291 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Mathematics in science and engineering ;  |v v. 73 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
506 |3 Use copy  |f Restrictions unspecified  |2 star  |5 MiAaHDL 
520 |a Adaptation and learning in automatic systems. 
533 |a Electronic reproduction.  |b [Place of publication not identified] :  |c HathiTrust Digital Library,  |d 2010.  |5 MiAaHDL 
538 |a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.  |u http://purl.oclc.org/DLF/benchrepro0212  |5 MiAaHDL 
583 1 |a digitized  |c 2010  |h HathiTrust Digital Library  |l committed to preserve  |2 pda  |5 MiAaHDL 
505 0 |a Front Cover; Adaptation and Learning in Automatic Systems; Copyright Page; Contents; Foreword; Preface to the English Edition; Preface to the Russian Edition; Introduction; Chapter 1. Problem of Optimality; 1.1 Introduction; 1.2 Criteria of Optimality; 1.3 More about the Criteria of Optimality; 1.4 Constraints; 1.5 A Priori and Current Information; 1.6 Deterministic and Stochastic Processes; 1.7 The Ordinary and Adaptive Approaches; 1.8 On Methods for Solving Optimization Problems; 1.9 Conclusion; Comments; Bibliography; Chapter 2. Algorithmic Methods of Optimization; 2.1 Introduction 
505 8 |a 2.2 Conditions of Optimality2.3 Regular Iterative Method; 2.4 Algorithms of Optimization; 2.5 A Possible Generalization; 2.6 Various Algorithms of Optimization; 2.7 Search Algorithms of Optimization; 2.8 Constraints I; 2.9 Constraints II; 2.10 The Method of Feasible Directions; 2.11 Discussion; 2.12 Multistage Algorithms of Optimization; 2.13 Continuous Algorithms of Optimization; 2.14 Methods of Random Search; 2.15 Convergence and Stability; 2.16 The Conditions of Convergence; 2.17 On Acceleration of Convergence; 2.18 On Best Algorithms; 2.19 Examples; 2.20 Certain Problems; 2.21 Conclusion 
505 8 |a CommentsBibliography; Chapter 3. Adaptation and Learning; 3.1 Introduction; 3.2 Concepts of Learning, Self-Learning and Adaptation; 3.3 Formulation of the Problem; 3.4 Probabilistic Iterative Methods; 3.5 Algorithms of Adaptation; 3.6 Search Algorithms of Adaptation; 3.7 Constraints I; 3.8 Constraints II; 3.9 A Generalization; 3.10 Multistage Algorithms of Adaptation; 3.11 Continuous Algorithms; 3.12 Probabilistic Convergence and Stability; 3.13 Conditions of Convergence; 3.14 Stopping Rules; 3.15 Acceleration of Convergence; 3.16 Measure of Quality for the Algorithms 
505 8 |a 3.17 The Best Algorithms3.18 Simplified Best Algorithms; 3.19 A Special Case; 3.20 Relationship to the Least-Square Method; 3.21 Relationship to the Bayesian Approach; 3.22 Relationship to the Maximum Likelihood Method; 3.23 Discussion; 3.24 Certain Problems; 3.25 Conclusion; Comments; Bibliography; Chapter 4. Pattern Recognition; 4.1 Introduction; 4.2 Discussion of the Pattern Recognition Problem; 4.3 Formulation of the Problem; 4.4 General Algorithms of Training; 4.5 Convergence of the Algorithms; 4.6 Perceptrons; 4.7 Discrete Algorithms of Training; 4.8 Search Algorithms of Training 
505 8 |a 4.9 Continuous Algorithms of Training4.10 Comments; 4.11 More about Another General Algorithm of Training; 4.12 Special Cases; 4.13 Discussion; 4.14 Self-Learning; 4.15 The Restoration of Probability Density Functions and Moments; 4.16 Algorithms of Restoration; 4.17 Principle of Self-Learning; 4.18 Average Risk; 4.19 Variation of the Average Risk; 4.20 The Conditions for the Minimum of the Average Risk; 4.21 Algorithms of Self-Learning; 4.22 A Generalization; 4.23 Specific Algorithms; 4.24 Search Algorithms of Self-Learning; 4.25 Discussion; 4.26 Certain Problems; 4.27 Conclusion; Comments 
650 0 |a Adaptive control systems. 
650 0 |a Self-organizing systems. 
650 6 |a Syst�emes adaptatifs.  |0 (CaQQLa)201-0010969 
650 6 |a Syst�emes auto-organis�es.  |0 (CaQQLa)201-0005928 
650 7 |a TECHNOLOGY & ENGINEERING  |x Automation.  |2 bisacsh 
650 7 |a TECHNOLOGY & ENGINEERING  |x Robotics.  |2 bisacsh 
650 7 |a Adaptive control systems.  |2 fast  |0 (OCoLC)fst00796490 
650 7 |a Self-organizing systems.  |2 fast  |0 (OCoLC)fst01111791 
776 0 8 |i Print version:  |a �T�Sypkin, �I�A. Z. (�I�Akov Zalmanovich).  |s Adapta�t�si�i�a i obuchenie v avtomaticheskikh sistemakh. English.  |t Adaptation and learning in automatic systems.  |d New York : Academic Press, 1971  |z 9780127020501  |w (DLC) 78129017  |w (OCoLC)141606 
830 0 |a Mathematics in science and engineering ;  |v v. 73. 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780127020501  |z Texto completo 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/publication?issn=00765392&volume=73  |z Texto completo 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/bookseries/00765392/73  |z Texto completo