Event-triggered network-based synchronization of delayed neural networks

Event-triggered network-based synchronization of delayed neural networks
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延迟神经网络的基于事件触发网络的同步

DOI:
10.1016/j.neucom.2016.01.022
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发表时间:
2016-05
期刊:
影响因子:
6
通讯作者:
Zhang Baoyong
Zhang Baoyong
中科院分区:
计算机科学2区
文献类型:
--
作者:
Lang Junpeng;Zhang Yijun;Zhang Baoyong

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本文关注一类延迟神经网络的事件触发网络同步问题。通过在控制环中引入事件发生器,构建了事件触发的主从同步帧模型。考虑通信网络的传输延迟和随机波动等影响,制定了主系统和从系统的事件触发错误系统。利用Lyapunov泛函方法,提出了一些线性矩阵不等式方面的时延相关同步准则,以确保主系统和从系统之间的均方同步。与以往文献不同,引入奇异值分解引理来解决神经元激活函数下界非零情况下的控制设计问题。提供了两个说明性示例来证明使用所提出的设计方案可以节省有限的网络带宽。
This paper is concerned with the problem of event-triggered network-based synchronization for a class of delayed neural networks. By introducing an event generator in the control loop, the model of event-triggered master–slave synchronization frame is constructed. Considering the effect of the communication network including transmission delay and stochastic fluctuation, an event-triggered error system of master system and slave system is formulated. By using the Lyapunov functional method, some delay-dependent synchronization criteria in terms of linear matrix inequality are proposed to ensure the mean square synchronization between the master system and the slave system. A singular value decomposition lemma is introduced to solve the control design problem for the case of the lower bound of neuron activation function is nonzero, which is different from the previous literature. Two illustrative examples are provided to demonstrate the limited network bandwidth could be saved by using the proposed design scheme.
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