GENERALIZED LEARNING RULE FOR HIGH-ORDER NEURAL NETWORKS

被引：4

作者：

MATUS, IJ

PEREZ, P

机构：

[1] Departamento de Fisica, Universidad de Santiago de Chile, Santiago, Correo 2

来源：

PHYSICAL REVIEW A | 1991年 / 43卷 / 10期

关键词：

D O I：

10.1103/PhysRevA.43.5683

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

We present a generalized learning rule valid for neurons having membrane potentials with a high-order dependence on the firing rates. The stability of the memorized states is investigated by studying the minima of an energy function. Our estimations of the capacity of memory are in qualitative agreement with results already known from the literature.

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页码：5683 / 5688

页数：6

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