Stability and Hopf bifurcation in a simplified BAM neural network with two time delays.
Various local periodic solutions may represent different classes of storage patterns or memory patterns, and arise from the different equilibrium points of neural networks (NNs) by applying Hopf bifurcation technique. In this paper, a bidirectional associative memory NN with four neurons and multiple delays is considered. By applying the normal form theory and the center manifold theorem, analysis of its linear stability and Hopf bifurcation is performed. An algorithm is worked out for determining the direction and stability of the bifurcated periodic solutions. Numerical simulation results supporting the theoretical analysis are also given.
Cao
Jinde
J
Department of Mathematics, Southeast University, Nanjing 210096, China. jdcao@seu.edu.cn
Xiao
Min
M
D000465:Algorithms; D001185:Artificial Intelligence; D005246:Feedback; D016247:Information Storage and Retrieval / Q000379:methods*; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D013997:Time Factors