A New Stability Condition of Discrete Hopfield Neural Networks with Weight Function Matrix

Abstract

The stability analysis of discrete Hopfield neural networks(DHNNs) not only has an important theoretical significance, but also can be widely used in the associative memory, combinatorial optimization, etc. Most matrixes of DHNNs and DHNNs with delay are constant matrixes. The stability of discrete Hopfield neural networks with weight function matrix (DHNNWFM) is studied. A new stability condition for DHNNWFM is presented by using the Lyapunov method.