Robust stability of delayed reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales

摘要

In this paper, the global robust exponential stability of equilibrium solution to delayed reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales is studied. Using topological degree theory, M-matrix method, Lyapunov functional and inequality skills, we establish some sufficient conditions for the existence, uniqueness and global robust exponential stability of equilibrium solution to delayed reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales. One example is given to illustrate the effectiveness of our results.