Author:
Luan Yifeng,Xiao Min,Yang Xinsong,Du Xiangyu,Ding Jie,Cao Jinde
Abstract
AbstractIn this paper, a two-neuron reaction–diffusion neural network with discrete and distributed delays is proposed, and the state feedback control strategy is adopted to achieve control of its spatiotemporal dynamical behaviours. Adding two virtual neurons, the original system is transformed into a neural network only containing the discrete delay. The conditions under which Hopf bifurcation and Turing instability arise are determined through analysis of the characteristic equation. Additionally, the amplitude equations are derived with the aid of weakly nonlinear analysis, and the selection of the Turing patterns is determined. The simulation results demonstrate that the state feedback controller can delay the onset of Hopf bifurcation and suppress the generation of Turing patterns.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province of China
Postgraduate Research and Practice Innovation Program of Jiangsu Province
Publisher
Springer Science and Business Media LLC