Controlling stability through the rate of decay of the delay feedback kernels

Abstract

Of concern is the Hopfield neural network system comprising discrete as well as distributed delays in the form of a convolution. For a desired convergence rate of the solution to the equilibrium state, we establish sufficient conditions on the delay kernels ensuring this matter. Our result improves an existing one in the literature. The adopted approach is completely different. It relies on a judicious choice of a Lyapunov-like function and careful manipulations.

Keywords

• hopfield neural network system
• discrete delay
• distributed delay
• exponentail stability
• arbitrary stability
• lyapunov-type function