Associative dynamics of color images in a large-scale chaotic neural network
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概要
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In this paper, we report a way to store color images in a large-scale chaotic neural network and to retrieve them by using chaotic dynamics. In the proposed method, color images are converted to binary codes, modified slightly by inverting a few bits, and stored in the network. The results of numerical simulations show that chaotic transitions among stored patterns and their reverse patterns can be observed within a certain range of parameters. We also compare five different coding schemes of color information, which change the appearance of chaotic dynamics. In addition, if connections are restricted in a neighborhood of each unit, a variety of wave patterns are observed.
著者
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Aihara Kazuyuki
Department Of Complex Science And Engineering Graduate School Of Frontier Science University Of Toky
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Oku Makito
Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
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