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Titlebook: Competition and Cooperation in Neural Nets; Proceedings of the U Shun-ichi Amari (Co-Organizer),Michael A. Arbib (C Conference proceedings

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书目名称Competition and Cooperation in Neural Nets
副标题Proceedings of the U
编辑Shun-ichi Amari (Co-Organizer),Michael A. Arbib (C
视频video
丛书名称Lecture Notes in Biomathematics
图书封面Titlebook: Competition and Cooperation in Neural Nets; Proceedings of the U Shun-ichi Amari (Co-Organizer),Michael A. Arbib (C Conference proceedings
描述The human brain, wi th its hundred billion or more neurons, is both one of the most complex systems known to man and one of the most important. The last decade has seen an explosion of experimental research on the brain, but little theory of neural networks beyond the study of electrical properties of membranes and small neural circuits. Nonetheless, a number of workers in Japan, the United States and elsewhere have begun to contribute to a theory which provides techniques of mathematical analysis and computer simulation to explore properties of neural systems containing immense numbers of neurons. Recently, it has been gradually recognized that rather independent studies of the dynamics of pattern recognition, pattern format::ion, motor control, self-organization, etc. , in neural systems do in fact make use of common methods. We find that a "competition and cooperation" type of interaction plays a fundamental role in parallel information processing in the brain. The present volume brings together 23 papers presented at a U. S. -Japan Joint Seminar on "Competition and Cooperation in Neural Nets" which was designed to catalyze better integration of theory and experiment in these ar
出版日期Conference proceedings 1982
关键词Neurokybernetik; behavior; cortex; information processing; neural mechanisms; neural network; neurons
版次1
doihttps://doi.org/10.1007/978-3-642-46466-9
isbn_softcover978-3-540-11574-8
isbn_ebook978-3-642-46466-9Series ISSN 0341-633X Series E-ISSN 2196-9981
issn_series 0341-633X
copyrightSpringer-Verlag Berlin Heidelberg 1982
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X-Ray Reflectivity and Surface Roughness,elation existing between a prey and a predator species, we simplify the relation itself by neglecting the influence of the remaining species or by representing such influence just by means of some parameters.
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Sigmoidal Systems and Layer Analysis for the mathematical analysis of the neural models. Indeed, some parts of the theory, dealing for example with small-amplitude phenomena, have already been extended to the latter context (Ermentrout 1980; Ermentrout and Cowan 1979, 1980a, 1980b).
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Competitive and Cooperative Aspects in Dynamics of Neural Excitation and Self-Organization and cooperation in an abstract field of a signal space. A field theory of self-organization is proposed and the behaviors of self-organizing nerve nets are analyzed from this unified point of view. The formation of topographic structures is elucidated by this method.
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Nerve Pulse Interactionsndrodendritic interactions [15]. Such suggestions have led Waxman to propse the concept of a “multiplex neuron” [16] which bears about the same relationship to a linear threshold unit as does a “chip” to a “gate” in modern integrated circuit technology.
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Systems Matching and Topographic Maps: The Branch-Arrow Model (BAM)ords well with most of the data, we shall present evidence that indicates the need for an additional mechanism, interaction between the branches and the tectal surface. A model of this kind, the Extended Branch Arrow Model (XBAM), will be described in a sequel.
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