A CONDITION FOR GLOBAL CONVERGENCE OF A CLASS OF SYMMETRICAL NEURAL CIRCUITS

被引：66

作者：

FORTI, M

MANETTI, S

MARINI, M

机构：

[1] Electronic Engineering Department, University of Florence, 50139, Firenze

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS | 1992年 / 39卷 / 06期

关键词：

D O I：

10.1109/81.153645

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A sufficient condition is proved guaranteeing that a class of neural circuits that includes the Hopfield model as a special case is globally convergent towards a unique stable equilibrium. The condition only requires symmetry and negative semi-definiteness of the neuron connection matrix T and is extremely simple to check and apply in practice. The consequences of the above result are discussed in the context of neural circuits for optimization of quadratic cost functions.

引用

页码：480 / 483

页数：4

共 11 条

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