Dissipativity of Stochastic Competitive Neural Networks with Multiple Time Delays
Dandan Tang, Baoxian Wang, Caiqing Hao · Neural Processing Letters · 2024
Abstract The $$(Q,R,S)-\gamma -$$ ( Q , R , S ) - γ - dissipative of stochastic competitive neural networks (SCNNs) with leakage delays and discrete delay is studied. Firstly, Lyapunov–Krasovskii functional is constructed, which studies the relationship between various types of time delays. Secondly, by using integral inequality technique, the linear matrix inequality (LMI) criterion of $$(Q,R,S)-\gamma -$$ ( Q , R , S ) - γ - dissipative in the mean square sense of SCNNs is obtained. Furthermore, the obtained LMI criterion is extended to the passivity in the mean square sense, stability in the mean square sense, $$(Q,R,S)-\gamma -$$ ( Q , R , S ) - γ - dissipative and passivity. Finally, the effectiveness of the obtained results are verified by numerical simulation.