Nonlinear Master Equation Approach to Asymmertrica Neural Networks of the Hopfield-Hemmen Type
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概要
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Dynamical properties of the Hopfield-Hemmen-type neural networks with asym-metrical synaptic connections are studied using a nonlinear nnaster equation which isobtained in the thermodynamic limit from the Glauber dynamics assumed for the networks. A self-consistent equation is derived for the time evolution of the overlaps ofthe instantaneous configuration with the built-in patterns of a finite number p. Twofundamental types of conditions for the occurrence of limit cycle-type oscillation ofthe pattern overlaps are presented for the case of p=2.[Hopfield-Hemmen model, neural network, Gla'uber dynamics, nonlinear master lj equation, limit cycle, nonequilibrium phase transitionl
- 社団法人日本物理学会の論文
- 1989-03-15
著者
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ONO MASAYA
Department of Surgery, Jichi Medical School
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Ono Masaya
Department Of Applied Physics
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NISHIMORI Hidetoshi
Department of Physics,Tokyo Institute of Technology
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Shiino Masatoshi
Department of Applied Physics
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Nishimori Hidetoshi
Department Of Physics Tokyo Institute Of Technology
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Nishimori Hidetoshi
Department Of Physics Facuilty Of Science Tokyo Institute Of Technology
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