IEEE Trans Neural Netw Learn Syst. 2016 Jan;27(1):190-201. doi: 10.1109/TNNLS.2015.2475737. Epub 2015 Oct 15.
This paper deals with the exponential synchronization of coupled stochastic memristor-based neural networks with probabilistic time-varying delay coupling and time-varying impulsive delay. There is one probabilistic transmittal delay in the delayed coupling that is translated by a Bernoulli stochastic variable satisfying a conditional probability distribution. The disturbance is described by a Wiener process. Based on Lyapunov functions, Halanay inequality, and linear matrix inequalities, sufficient conditions that depend on the probability distribution of the delay coupling and the impulsive delay were obtained. Numerical simulations are used to show the effectiveness of the theoretical results.
本文研究了具有概率时变时滞耦合和时变脉冲时滞的耦合随机忆阻神经网络的指数同步问题。在延迟耦合中存在一个概率传输延迟,由满足条件概率分布的伯努利随机变量转换。干扰由维纳过程描述。基于李雅普诺夫函数、Halanay 不等式和线性矩阵不等式,得到了依赖于延迟耦合和脉冲延迟的概率分布的充分条件。数值模拟结果表明了理论结果的有效性。