New Criteria on Stability Analysis of Generalized Neural Networks With Time-Varying Delays
Wei-Min Wang, Yan‐Wu Wang · IEEE Transactions on Systems Man and Cybernetics Systems · 2025
The stability problem of generalized neural networks (GNNs) with time-varying delay is investigated in this article. Novel parameter-dependent negative-determination conditions (NDCs) for cubic matrix-valued polynomials are derived by using convex approaches. In comparison with the existing methods, the positive-definite constraint on the constructed Lyapunov–Krasovskii functional (LKF) is relaxed by using the sum of several matrices to maintain positive definiteness instead of this requirement on every single matrix involved in the LKF. Less conservative stability conditions are established by using the constructed LKF and the proposed parameter-dependent NDCs for cubic matrix-valued polynomials. Two examples, including comparative results to existing methods are presented to show the feasibility and superiority of the proposed method.