Multistability of Recurrent Neural Networks With Time-varying Delays and the Piecewise Linear Activation Function

摘要

In this brief, stability of multiple equilibria of recurrent neural networks with time-varying delays and the piecewise linear activation function is studied. A sufficient condition is obtained to ensure that $n$-neuron recurrent neural networks can have $(4k-1)^{n}$ equilibrium points and $(2k)^{n}$ of them are locally exponentially stable. This condition improves and extends the existing stability results in the literature. Simulation results are also discussed in one illustrative example.