Bipartite quasi-synchronization of multiple neural networks with generalized cooperative-competitive topology

This study examines the bipartite quasi-synchronization(B-Q synchronization)issue of coupled networks with general cooperative-competitive topology and the event-triggered communications between nodes to curb the communication cost.In the existing literature concerning bipartite synchronization,the network topology is required to be structurally balanced,which necessitates that competitive interactions exist only between two distinct subgroups.In this study,we aim to lengthen the network’s topology to a more general signed network in which antagonistic interactions can exist in the same or different subgroups.According to signed graph theory and the markovian stochastic event-triggering mechanism,the dynamical model of multiple neural networks(MNNs)with structurally unbalanced and markovian event-triggered communication is established.By utilizing the stochastic Lyapunov stability analysis,some adequate criteria for B-Q synchronization of MNNs with the structurally unbalanced graph are obtained;also,a bound for the B-Q synchronization error is provided.As a special case,the bipartite synchronization criteria for MNNs with the structurally balanced graph are also obtained.Finally,two simulations are performed to verify the theoretical result.