STABILITY ANALYSIS OF DYNAMICAL NEURAL NETWORKS

In this paper, we use the matrix measure technique to study stability of dynamical neural networks. Testable conditions for global exponenti al stability of nonlinear dynamical systems and dynamical neural netwo rks are given, It shows how a few well-known results can be unified an d generalized in a straightforward way, Local exponential stability of a class of dynamical neural networks is also studied; we point out th at the local exponential stability of any equilibrium point of dynamic al neural networks is equivalent to the stability of the linearized sy stem around that equilibrium point, From this, some well-known and new , sufficient conditions for local exponential stability of neural netw orks are obtained.