Self-excitation of neurons leads to multiperiodicity of discrete-time neural networks with distributed delays
Huang Zhen · 2011
In this paper, we investigate the interesting multiperiodicity of discrete-time neural networks with excitatory self-connections and distributed delays. Due to self-excitation of neurons, we construct 2N close regions in state space for N-dimensional networks and attain the coexistence of 2N periodic sequence solutions in these close regions. Meanwhile we estimate exponential attracting domain for each periodic sequence solution and apply our results to discrete-time analogues of periodic or autonomous neural networks. Under self-excitation of neurons, numerical simulations are performed to illustrate the effectiveness of our results.