Chaotic Behavior for Asymmetrically Diluted Hopfield Neural Network with a Non-Monotonic Transfer Function(General)

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概要

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• We investigate retrieval properties for a synchronous asymmetrically diluted Hopfield neural network with a non-monotonic transfer function by an analytic method. Because of asymmetry of interaction and non-monotonicity of the transfer function, it is difficult to use conventional methods of the equilibrium statistical mechanics in order to investigate the network. We therefore use a generating-function method of path-integral representation, and then obtain an equation for a dynamical order parameter. We find chaotic behavior for the retrieval overlap by choosing a threshold adequately; a Lyapunov exponent is positive in that case. We clarify a bifurcation diagram in a plane specified by a threshold and a load parameter at zero temperature.

• 社団法人日本物理学会の論文
• 2006-04-15

著者

• Horiguchi Tsuyoshi

  Educational Counseling Office School Of Engineering Tohoku University

• Katayama Katsuki

  Department Of Computer Science And Systems Engineering Faculty Of Engineering Muroran Institute Of T

• Katayama Katsuki

  Department Of Computer And Mathematical Sciences Graduate School Of Information Sciences Tohoku Univ

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• Chaotic Behavior for Asymmetrically Diluted Hopfield Neural Network with a Non-Monotonic Transfer Function(General)

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