Stability analysis of impulsive stochastic reaction-diffusion cellular neural network with distributed delay via fixed point theory
Summary: This paper investigates the stochastically exponential stability of reaction-diffusion impulsive stochastic Cellular Neural Networks (CNN). The reaction-diffusion pulse stochastic system model characterizes the complexity of practical engineering and brings about mathematical difficulties, too. However, the difficulties have been overcome by constructing a new contraction mapping and an appropriate distance on a product space which is guaranteed to be a complete space. This is the first time to employ the fixed-point theorem to derive the stability criterion of reaction-diffusion impulsive stochastic CNN with distributed time delays. Finally, an example is provided to illustrate the effectiveness of the proposed methods.
reaction-diffusion impulsive stochastic cellular neural networks (CNN)
scientific article; zbMATH DE number 6822324
scientific article