IEEE Trans Neural Netw Learn Syst - Graph Theory-Based Approach for Stability Analysis of Stochastic Coupled Systems With L?vy Noise on Networks.

Tópicos

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Resumo

In this paper, a novel class of stochastic coupled systems with L?vy noise on networks (SCSLNNs) is presented. Both white noise and L?vy noise are considered in the networks. By exploiting graph theory and Lyapunov stability theory, criteria ensuring p th moment exponential stability and stability in probability of these SCSLNNs are established, respectively. These principles are closely related to the topology of the network and the perturbation intensity of white noise and L?vy noise. Moreover, to verify the theoretical results, stochastic coupled oscillators with L?vy noise on a network and stochastic Volterra predator-prey system with L?vy noise are performed. Finally, a numerical example about oscillators' network is provided to illustrate the feasibility of our analytical results.

Resumo Limpo

paper novel class stochast coupl system lvi nois network scslnns present white nois lvi nois consid network exploit graph theori lyapunov stabil theori criteria ensur p th moment exponenti stabil stabil probabl scslnns establish respect principl close relat topolog network perturb intens white nois lvi nois moreov verifi theoret result stochast coupl oscil lvi nois network stochast volterra predatorprey system lvi nois perform final numer exampl oscil network provid illustr feasibl analyt result

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