Stability of a Class of Neural Networks with Asymmetric Connection Weights

摘要

This paper derives some sufficient conditions for exponential stability for the equilibrium point by dividing the state variables of the system according to the characters of the neural networks. The new conditions are described by some blocks of the interconnection matrix. An example is given to demonstrate the effectiveness of the proposed theory.