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Learning Algorithms Theory and Applications: Theory and Applications Softcover Repri Edition
Contributor(s): Lakshmivarahan, S. (Author)

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 ISBN: 0387906401     ISBN-13: 9780387906409
Publisher: Springer
OUR PRICE: $52.24  

Binding Type: Paperback - See All Available Formats & Editions
Published: November 1981
Qty:
Additional Information
BISAC Categories:
- Reference | Questions & Answers
- Mathematics | Number Systems
- Mathematics | Numerical Analysis
Dewey: 001.535
LCCN: 81016683
Physical Information: 0.63" H x 6.14" W x 9.21" L (0.93 lbs) 280 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
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.
 
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