LMI-Based Results on Robust Exponential Passivity of Uncertain Neutral-Type Neural Networks with Mixed Interval Time-Varying Delays via the Reciprocally Convex Combination Technique

The issue of the robust exponential passivity analysis for uncertain neutral-type neural networks with mixed interval time-varying delays is discussed in this work. For our purpose, lower bounds are allowed to be either positive or zero adopting combination model transformation, various inequalities, reciprocally convex combination, and suitable Lyapunov–Krasovskii functional. A new criterion received formulated form linear matrix inequalities (LMIs). Moreover, a also examined systems without uncertainty. Four numerical examples indicate potential results exceed previous results.