Learning Algorithms Theory and Applications - S. Lakshmivarahan - 書籍 - Springer-Verlag New York Inc. - 9780387906409 - 1981年11月2日
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S. Lakshmivarahan
Learning Algorithms Theory and Applications Softcover Reprint of the Original 1st Ed. 1981 edition

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Learning constitutes one of the most important phase of the whole psychological processes and it is essential in many ways for the occurrence of necessary changes in the behavior of adjusting organisms. In a broad sense influence of prior behavior and its consequence upon subsequent behavior is usually accepted as a definition of learning. Till recently learning was regarded as the prerogative of living beings. But in the past few decades there have been attempts to construct learning machines or systems with considerable success. This book deals with a powerful class of learning algorithms that have been developed over the past two decades in the context of learning systems modelled by finite state probabilistic automaton. These algorithms are very simple iterative schemes. Mathematically these algorithms define two distinct classes of Markov processes with unit simplex (of suitable dimension) as its state space. The basic problem of learning is viewed as one of finding conditions on the algorithm such that the associated Markov process has prespecified asymptotic behavior. As a prerequisite a first course in analysis and stochastic processes would be an adequate preparation to pursue the development in various chapters.

280 pages, biography

メディア 書籍     Paperback Book   (ソフトカバーで背表紙を接着した本)
リリース済み 1981年11月2日
ISBN13 9780387906409
出版社 Springer-Verlag New York Inc.
ページ数 280
寸法 155 × 235 × 16 mm   ·   421 g
言語 英語  

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