摘要
主要讨论一类具有反应扩散项混合时滞耦合神经网络的同步问题.同时,考虑系统参数的范数有界不确定性及其切换依赖某个马尔可夫链等方面对其的影响.文中通过构造新颖的Lyapunov-Krasovskii泛函,运用线性矩阵不等式(LMI)技术并结合Kronecker积来获得耦合神经网络的鲁棒均方全局指数同步的充分性条件,并且所获得的判据依赖于时滞.该条件可由MATLAB的LMI工具箱进行有效的验证.此外,细胞激活函数更为一般的假设,可进一步减少结论的保守性.
This paper discusses an array of stochastic coupled neural networks with mixed time delays and reaction-diffusion terms,and considering norm-bounded uncertainties and markovian switching.Also,by employing a novel Lyapunov-Krasovskii functional,and conducting a linear matrix inequality(LMI) approach,Kronecker product is developed to derive the criteria for the synchronization,which can be readily checked by using the MATLAB LMI Toolbox.Furthermore,the description of the activation functions is more general and therefore less conservative on the criteria of synchronization.
出处
《生物数学学报》
2015年第2期344-364,共21页
Journal of Biomathematics
基金
国家自然科学基金(61174021
61074129)
江苏省自然科学基金(BK20131109)
关键词
耦合神经网络
不确定性
反应扩散项
混合时滞
随机扰动
马尔可夫转换
鲁棒全局均方指数同步
线性矩阵不等式
Coupled neural network
Uncertain
Reaction-diffusion Terms
Mixed time delays
Stochastic disturbance
Markovian switching
Robust exponential mean square synchronization
Linear matrix inequality
