New delay and order-dependent passivity criteria for impulsive fractional-order neural networks with switching parameters and proportional delays

This work deals with the problem of passivity analysis of fractional-order neural networks (FONNs) with impulse, proportional delays and state-dependent switching parameters. The novelty of the work lies in addressing the crucial issue of developing a delay-dependent LMI condition for analysing the behaviour of delayed FONNs. In this paper, a new lemma on Caputo fractional derivatives is developed to construct a new Lyapunov functional to derive delay dependent LMI condition for the passivity analysis of FONNs. Besides that, under modification, another sufficient condition is derived to give an impulse gain dependent LMI condition. Moreover, for the first time in the literature, delay-dependent and order dependent passivity criteria for fractional-order systems with proportional delays are presented in this paper. Finally, the results obtained are verified with suitable numerical parameter values and the simulation results are demonstrated to show the effectiveness of the proposed method and superiority of FONNs. (c) 2021 Published by Elsevier B.V.

Automated summary

This work presents a novel delay-dependent LMI condition for analyzing the passivity of fractional-order neural networks with impulse, proportional delays, and state-dependent switching parameters. Additionally, a sufficient condition for impulse gain-dependent LMI condition is derived, along with passivity criteria for fractional-order systems with proportional delays.