Dissipativity and Passivity analysis of neural networks with mixed-time-varying delays

FINITE-TIME PASSIVITY OF DISCRETE-TIME T-S FUZZY NEURAL NETWORKS WITH TIME-VARYING DELAYS

This paper focuses on the problem of finite-time boundedness and finite-time passivity of discrete-time T-S fuzzy neural networks with time-varying delays. A suitable Lyapunov--Krasovskii functional(LKF) is established to derive sufficient condition for finite-time passivity of discrete-time T-S fuzzy neural networks. The dynamical system is transformed into a T-S fuzzy model with uncertain par...

Dissipativity and passivity analysis for discrete-time complex-valued neural networks with time-varying delay

Abstract: In this paper, we consider the problem of dissipativity and passivity analysis for complex-valued discrete-time neural networks with time-varying delays. The neural network under consideration is subject to time-varying. Based on an appropriate Lyapunov–Krasovskii functional and by using the latest free-weighting matrix method, a sufficient condition is established to ensure that the ...

Stochastic Passivity of Uncertain Neural Networks with Time-Varying Delays

and Applied Analysis 3 dx t [ − C ΔC t x t A ΔA t f x t B ΔB t f x t − τ t u t ] dt σ t, x t , x t − τ t dω t 2.1 for t ≥ 0, where x t x1 t , x2 t , . . . , xn t T ∈ R is the state vector of the network at time t, n corresponds to the number of neurons; C diag c1, c2, . . . , cn is a positive diagonal matrix, A aij n×n, and B bij n×n are known constant matrices; ΔC t , ΔA t and ΔB t are time-va...

Global point dissipativity of neural networks with mixed time-varying delays.

By employing the Lyapunov method and some inequality techniques, the global point dissipativity is studied for neural networks with both discrete time-varying delays and distributed time-varying delays. Simple sufficient conditions are given for checking the global point dissipativity of neural networks with mixed time-varying delays. The proposed linear matrix inequality approach is computatio...

lobal point dissipativity of neural networks ith mixed time-varying delays