AVERAGED NEURAL NETWORKS

被引:43
作者
BURTON, TA
机构
[1] Southern Illinois Univ at Carbondale, Carbondale, United States
关键词
COHEN-GROSSBERG SYSTEM; HOPFIELD SYSTEM; LIAPUNOV FUNCTIONS; STABILITY;
D O I
10.1016/S0893-6080(05)80111-X
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cohen and Grossberg studied an almost gradient system of ordinary differential equations with application to neural networks and used a Liapunov function, together with an invariance principle, to show that some equilibrium points attract solutions. Independently, Hopfield modeled a neural network by means of a system of ordinary differential equations which turn out to be a special case of the Cohen-Grossberg system, as pointed out by Cohen. In the Hopfield model it is clear thal the functions involved in the equations are averages and that current will flow through a synapse only ifa certain threshold is reached; however, none of the models take into account an averaging technique. Investigators have been interested in sustained oscillations in neural networks and have produced them in computer simulations when there is a pointwise delay. The linearized systems with a delay have also exhibited sustained oscillations. But our conjecture is that oscillations are not caused by a delay. This paper is intended to put substance to that conjecture by examining models with both pointwise and distributed delays. None of the models have solutions with sustained oscillations.
引用
收藏
页码:677 / 680
页数:4
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