Multistability of Recurrent Neural Networks With Time-varying Delays and the Piecewise Linear Activation Function
Zhigang Zeng, Tingwen Huang, Wei Xing Zheng · IEEE Transactions on Neural Networks · 2010
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.