title: Robust exponential stability of uncertain stochastic neural networks with distributed delays and reaction-diffusions.
abstract: This paper considers the problem of stability analysis for uncertain stochastic neural networks with distributed delays and reaction-diffusions. Two sufficient conditions for the robust exponential stability in the mean square of the given network are developed by using a Lyapunov-Krasovskii functional, an integral inequality, and some analysis techniques. The conditions, which are expressed by linear matrix inequalities, can be easily checked. Two simulation examples are given to demonstrate the reduced conservatism of the proposed conditions.
authors.forename: Jianping
authors.initials: J
authors.lastname: Zhou
authors.forename: Shengyuan
authors.initials: S
authors.lastname: Xu
authors.forename: Baoyong
authors.initials: B
authors.lastname: Zhang
authors.forename: Yun
authors.initials: Y
authors.lastname: Zou
authors.forename: Hao
authors.initials: H
authors.lastname: Shen
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004058:Diffusion; D005246:Feedback; D015233:Models, Statistical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D013269:Stochastic Processes