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Received:August 01, 2015 Revised:September 28, 2015
Received:August 01, 2015 Revised:September 28, 2015
中文摘要: 在实现实际的复杂人工神经网络模型以及大规模集成电路时,随机噪声是不可避免的.因此,随机忆阻器神经网络具有重要的现实研究意义.针对变时滞随机忆阻器神经网络的同步控制问题,基于非光滑分析以及集值映射、随机微分包含的理论,利用Lyapunov函数和基本不等式的方法,设计了一个线性反馈控制器.通过恰当选择控制器增益,实现了随机忆阻器神经网络驱动系统与相应的响应系统之间的指数同步,所得到的结果保守性更小.最后,给出数值例子验证了理论结果的有效性.
中文关键词: 随机忆阻器神经网络 同步 变时滞 Lyapunov函数 非光滑分析
Abstract:Stochastic noise is unavoidable in the implementation of real complex artificial neural network model and large scale integrated circuit. Therefore, the practical research significance of stochastic memristor-based neural network is important. Aiming at the problem of synchronization control of stochastic memristor-based neural networks with time-varying delays, based on non-smooth analysis and the theory of set-valued maps and stochastic differential inclusions, a novel control method is given using the method of Lyapunov functional and the fundamental inequality. State feedback controller has been put forward to achieve synchronization index for the drive system and corresponding response system of the stochastic memristor-based neural network. Meanwhile, a numerical example is given to verify the theoretical analysis in this paper.
keywords: stochastic memristor-based neural networks synchronization time-varying delays Lyapunov functional non-smooth analysis
文章编号: 中图分类号: 文献标志码:
基金项目:
Author Name | Affiliation |
SHEN Jun | School of IoT Engineering, Jiangnan University, Wuxi 214000, China |
LOU Xu-Yang | School of IoT Engineering, Jiangnan University, Wuxi 214000, China |
Author Name | Affiliation |
SHEN Jun | School of IoT Engineering, Jiangnan University, Wuxi 214000, China |
LOU Xu-Yang | School of IoT Engineering, Jiangnan University, Wuxi 214000, China |
引用文本:
沈君,楼旭阳.变时滞随机忆阻器神经网络的同步控制.计算机系统应用,2016,25(4):23-28
SHEN Jun,LOU Xu-Yang.Synchronization Control of Stochastic Memristor-Based Neural Networks with Time-Varying Delays.COMPUTER SYSTEMS APPLICATIONS,2016,25(4):23-28
沈君,楼旭阳.变时滞随机忆阻器神经网络的同步控制.计算机系统应用,2016,25(4):23-28
SHEN Jun,LOU Xu-Yang.Synchronization Control of Stochastic Memristor-Based Neural Networks with Time-Varying Delays.COMPUTER SYSTEMS APPLICATIONS,2016,25(4):23-28