Exponential Stability of Positive Recurrent Neural Networks with Multi-proportional Delays

被引：16
|
作者：
Yang, Gang [1 ]
机构：
[1] Hunan Univ Commerce, Sch Math & Stat, Changsha 410205, Hunan, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2019年 / 49卷 / 01期
关键词：
Positive recurrent neural network; Generalized exponential stability; Proportional delay; ALMOST-PERIODIC SOLUTIONS;
D O I：
10.1007/s11063-018-9802-z
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents some new results on the existence, uniqueness and generalized exponential stability of a positive equilibrium for positive recurrent neural networks with multi-proportional delays. Based on the differential inequality techniques, a testable condition is established to guarantee that all solutions of the considered system converge exponentially to a unique positive equilibrium. The effectiveness of the obtained results is illustrated by a numerical example.
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页码：67 / 78
页数：12
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