Gap structure of the local field in symmetric Q Ising neural networks

被引：2

作者：

Bolle, D. ^{[1
]}

Shim, G.M. ^{[2
]}

机构：

[1] Instituut Voor Theoretische Fysica, Katholieke Universiteit Leuven, B-3001 Leuven, Belgium

[2] Department of Physics, Chungnam National University, Yuseong, Taejon 305-764, Korea, Republic of

来源：

Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | 2002年 / 65卷 / 06期

关键词：

Computer simulation - Gaussian noise (electronic) - Mathematical models - Maxwell equations - Neurology - Probability distributions - Signal to noise ratio - Thermodynamics;

D O I：

10.1103/PhysRevE.65.067101

中图分类号：

学科分类号：

摘要：

The time evolution of the local field in symmetric Q-Ising neural networks is studied for arbitrary Q. In particular, the structure of the noise and the appearance of gaps in the probability distribution are discussed. Results are presented for several values of Q and compared with numerical simulations. ©2002 The American Physical Society.

引用

页码：1 / 067101