The macroscopic dynamics in separable neural networks
无序系统与神经网络
2007-05-23 v1
摘要
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
引用
@article{arxiv.cond-mat/0209279,
title = {The macroscopic dynamics in separable neural networks},
author = {Yong Chen and Ying Hai Wang and Kong Qing Yang},
journal= {arXiv preprint arXiv:cond-mat/0209279},
year = {2007}
}
备注
5 pages