Dissipativity Analysis of Complex-Valued Stochastic Neural Networks With Time-Varying Delays
Meijuan Liu, Xiangrong Wang, Ziye Zhang, Zhen Wang · IEEE Access · 2019
This paper considers the dissipativity analysis problem for complex-valued stochastic neural networks (CVSNNs) with time-varying delays. By constructing the Lyapunov functions, using Jensen inequality and stochastic analysis techniques, several sufficient conditions for the exponential dissipativity and (Q, R, S)-dissipativity in the mean square are obtained in terms of linear matrix inequalities (LMIs). Compared with the existing ones, in our work, some results which are more applicable for CVSNNs with time-varying delays case are derived. Finally, two numerical examples are provided to illustrate the effectiveness and improvement of our theoretical results.