人工神经网络
算法
理论(学习稳定性)
计算机科学
区间(图论)
数学
人工智能
应用数学
机器学习
组合数学
作者
M. Syed Ali,Ramasamy Saravanakumar,Quanxin Zhu
标识
DOI:10.1016/j.neucom.2015.04.023
摘要
This paper deals with the robust H∞ control problem for a class of uncertain neural networks with discrete interval and distributed time-varying delays. The main purpose of this paper is to estimate robust asymptotic stability of the given neural network with H∞ performance analysis γ. By constructing novel Lyapunov–Krasovskii functionals with triple integral terms, several new less conservative delay-dependent stability conditions for H∞ control are obtained in terms of linear matrix inequalities. Numerical examples are given to illustrate the effectiveness of the proposed theoretical results. The method given in this paper shows less conservative results when comparing with some existing methods.
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