Existence and Global Exponential Stability of Equilibrium Solution to Reaction-Diffusion Recurrent Neural Networks on Time Scales

Existence and Global Exponential Stability of Equilibrium Solution to Reaction-Diffusion Recurrent Neural Networks on Time Scales

Blog Article

The existence of equilibrium solutions to reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales is proved baker mayfield wedding ring by the topological degree theory and M-matrix method.Under some sufficient conditions, we obtain the uniqueness and global exponential stability of equilibrium solution to reaction-diffusion recurrent neural networks with 392 cam kit Dirichlet boundary conditions on time scales by constructing suitable Lyapunov functional and inequality skills.One example is given to illustrate the effectiveness of our results.