Passivity And Synchronization Of Event-triggered Multi-weight Coupled Neural Networks

In recent years,complex networks have attracted more and more attentions due to their widespread applications in various fields,e.g.,communication networks,global economic markets,metabolic systems and so on.If each node denotes one neural network and each edge indicates an influence of one neural network on another one in a complex network,then this network is called coupled neural networks.Coupled neural network is a special type of complex networks,which has received more and more attention because of its extensive applications in diverse fields,such as harmonic oscillation generation,secure communication,chaos generators design.In practice,many systems,such as transportation networks,social networks,and so on,in the real world should be modeled by multi-weighted complex networks,in which the nodes are coupled through multiple coupling forms.Therefore,it is more practical to study the multi-weighted coupled neural network.In this paper,the passivity and synchronization of multi-weighted coupled neural networks model with event-triggered communication is studied by utilizing Lyapunov stability theory and some inequality techniques.Firstly,by employing some new inequality techniques and designing appropriate event-triggered controller and Lyapunov functional,some sufficient conditions for passivity and synchronization of multiweighted coupled neural network and multi-weighted coupled delayed neural network with event-triggered communication are established.Because of the environmental disturbance,noises and model errors,these elements are possible to cause the networks into unexpected states and even break the synchronization.Thus,we get some criteria for ensuring the H_? synchronization of multi-weighted coupled neural network and multiweighted coupled delayed neural network with event-triggered communication at the level of disturbance attenuation.Thirdly,due to the effect of environmental noise and model error,it is usually impossible to obtain the accurate value of parameters in many cases.Therefore,we also purse the study on the robust passivity,robust synchronization and robust H_? synchronization of multi-weighted coupled neural network and multiweighted coupled delayed neural network with parameter uncertainties,and present several event-triggered robust passivity,robust synchronization and robust H_?synchronization criteria for the considered network.At last,we provide some numerical examples to illustrate the effectiveness of the obtained criteria.