期刊论文

Adaptive Exponential Synchronization for Neutral-type Stochastic Neural Networks with Markovian Jumping Parameters

中文

湖南城市学院学报(自然科学版)

1672-7304

2020

29

3

47-51

10.3969/j.issn.1672-7304.2020.03.0011

11601140:国家自然科学基金 17B049:湖南省教育厅科学研究项目 19A092:湖南省教育厅科学研究项目 2017YZ14:益阳市科技计划

本校为第一机构

研究具有马氏切换参数的随机中立型神经网络的同步问题.基于Lyapunov稳定性理论、随机分析和自适应控制方法,在时滞是有界可测的前提下,提出了2个能保证中立型神经网络实现同步的时滞依赖充分性判据;同时,设计了依Markovian跳变的自适应更新律;最后通过算例证明了该理论的正确性.

Synchronization of stochastic neutral neural networks with Markovian switching parameters is studied.Based on the Lyapunov stability theory,stochastic analysis,and adaptive control method,on the premise that the time delay is bounded and measurable,two sufficient time delay dependence criteria that can guarantee the synchronization of the neutral neural network are proposed.At the same time,an adaptive update law based on Markovian jumps is designed.Finally,the c...