Passivity Analysis of Fractional-Order Neural Networks with Time-Varying Delay Based on LMI Approach

The Passivity of Uncertain Fractional-Order Neural Networks with Time-Varying Delays

“…For example, in [29], the robust finite-time passivity of UFONNs was studied, but the passivity of the system when time delays existed was not considered. In [38], the passivity of FONNs with time-varying delays was studied, but the uncertainties were not considered. In [45], the passivity of FONNs with time-varying parameter uncertainties was studied.…”

“…Therefore, compared with integer-order NNs, the passive research of FONNs is more challenging. Up to now, there have only been very few works that considered passivity [37,38]. In [37], the authors studied the passive problem of FONNs by means of an LMI technique and control theory; only the order-independent case was studied, and time delays were not considered.…”

“…When the delay is small, the delay-independent stability condition is less conservative. Very recently, the passivity of FONNs with time-varying delays was studied using an LMI technique and control theory in [38], where system uncertainties were not considered. However, the connection weight of a neuron depends on its capacitance and resistance values, including uncertainties, so it is very important to study the passivity of uncertain fractional-order neural networks (UFONNs).…”

Robust control for uncertain variable fractional order differential systems considering time‐varying delays and nonlinear perturbations

“…In addition to the fixed time delay, there are also time‐varying and distributed delays. The passivity analysis of fractional order neural networks with a time‐varying delay based on the Razumikhin fractional order theorem is discussed by Sau et al, 14 Badri et al, 15 and Chen et al 16 investigated the robust stability and stabilization analysis of fractional order systems with time‐varying delays. The problems of robust reliable optimization control for uncertain discrete‐time nonlinear Takagi‐Sugeno fuzzy systems with or without time‐varying delay subject to faults are investigated by Sun et al 17 Zhang et al 18 discussed the asymptotic stability of the Riemann–Liouville fractional order neural networks with discrete and distributed delays.…”

Passivity analysis of multiple time-varying time delayed complex variable neural networks in finite-time

“…The authors of [32] used the Lyapunov-Krasovskii functional approach and weighting matrices to study passivity analysis of stochastic time-delay neural networks. In addition, the subject of passivity analysis for various neural networks has received a lot of attention [33][34][35][36][37][38][39][40][41][42]. To the best of authors knowledge, so far, no result on the finite-time passivity for complex valued neural network systems with time varying delay has been reported.…”