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The macroscopic dynamics in separable neural networks

Yong Chen·Ying Hai Wang·Kong Qing Yang
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Abstract

The parallel dynamics is given in the case of neural networks with separable coupling through starting from Coolen-Sherrington (CS) theory. It is shown that this retrieve dynamics as is the case of sequential evolution in the postulate of away from saturation and finite temperature. The finite-size effects is governed by a homogeneous Markov process, which differs from the time-dependent Ornstein-Uhlenbeck process in sequential dynamics. PACS number(s): 87.10.+e, 75.10.Nr, 02.50.+s

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Yong Chen, Ying Hai Wang, Kong Qing Yang. 2002-09-12. The macroscopic dynamics in separable neural networks. https://arxiv.org/abs/cond-mat/0209279

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