Novel order-dependent passivity conditions of fractional generalized Cohen–Grossberg neural networks with proportional delays

Abstract

This work delves into the passivity of fractional generalized Cohen–Grossberg neural networks (CGNNs) with proportional delays. In particular, two forms of Lipschitz conditions for activation function are considered. Some passivity criteria are given by utilizing the Schur Complement lemma, Lyapunov–Krasovskii functional approach and Cauchy matrix inequality. The presented conditions are derived as matrix inequality forms and related to the proportional factor and order. This can clearly reflect the influence of the order and proportional factor on the input–output energy of the system. Two examples are particularized to better substantiate the obtained passivity results.