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Titlebook: Neural Networks Theory; Alexander I. Galushkin Book 2007 Springer-Verlag Berlin Heidelberg 2007 Applications of Fuzzy Logic.Fuzziness.Fuzz

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发表于 2025-3-21 19:29:46 | 显示全部楼层 |阅读模式
书目名称Neural Networks Theory
编辑Alexander I. Galushkin
视频video
概述Wonderful and important book from one of the leaders in neural network theory.A major contribution to the neural network literature.Includes forewords by Lotfi Zadeh, Robert Hecht Nielsen and Sun-Ichi
图书封面Titlebook: Neural Networks Theory;  Alexander I. Galushkin Book 2007 Springer-Verlag Berlin Heidelberg 2007 Applications of Fuzzy Logic.Fuzziness.Fuzz
描述."Neural Networks Theory is a major contribution to the neural networks literature. It is a treasure trove that should be mined by the thousands of researchers and practitioners worldwide who have not previously had access to the fruits of Soviet and Russian neural network research. Dr. Galushkin is to be congratulated and thanked for his completion of this monumental work; a book that only he could write. It is a major gift to the world."..Robert Hecht Nielsen, Computational Neurobiology, University of California, San Diego.."Professor Galushkin’s monograph has many unique features that in totality make his work an important contribution to the literature of neural networks theory. He and his publisher deserve profuse thanks and congratulations from all who are seriously interested in the foundations of neural networks theory, its evolution and current status."..Lotfi Zadeh, Berkeley, Founder of Fuzziness.."Professor Galushkin, a leader in neural networks theory in Russia, uses mathematical methods in combination with complexity theory, nonlinear dynamics and optimization, concepts that are solidly grounded in Russian tradition. His theory is expansive: covering not just the tradi
出版日期Book 2007
关键词Applications of Fuzzy Logic; Fuzziness; Fuzzy Logic; Matlab; Signal; algorithm; algorithms; architecture; ar
版次1
doihttps://doi.org/10.1007/978-3-540-48125-6
isbn_softcover978-3-642-08006-7
isbn_ebook978-3-540-48125-6
copyrightSpringer-Verlag Berlin Heidelberg 2007
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https://doi.org/10.1007/978-3-540-48125-6Applications of Fuzzy Logic; Fuzziness; Fuzzy Logic; Matlab; Signal; algorithm; algorithms; architecture; ar
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Introduction of modern elemental base technology that mainly determines the development of computer architecture, and second, practical requirements to solve specific problems in a faster and more economical manner.
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Continual Neural Networksn example is a design of a pattern recognition system with the requirement of maximum probability of correct recognition [.]. It is suggested to take into account continual properties of multilayer neural network characteristics in its mathematical modeling and in its technological implementation.
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Analysis of Closed-Loop Multilayer Neural Networks is implied that the open-loop neural network structure, the general characteristics of the signal, and the multilayer neural network adjustment algorithm are given. Several problems must be solved for the quality estimation of the closed-loop multilayer neural networks.
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