Stability of asymmetric Hopfield networks
Tianping Chen, Шун-ичи Амари · IEEE Transactions on Neural Networks · 2001
In this paper, we discuss dynamical behaviors of recurrently asymmetrically connected neural networks in detail. We propose an effective approach to study global and local stability of the networks. Many of well known existing results are unified in our framework, which gives much better test conditions for global and local stability. Sufficient conditions for the uniqueness of the equilibrium point and its stability conditions are given, too.