Exponential stability of continuous-time and discrete-time cellular neural networks with delays
Applied Mathematics and Computation
Automatica (Journal of IFAC)
Brief paper: New delay-dependent stability criteria for systems with interval delay
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Delay-derivative-dependent stability for delayed neural networks with unbound distributed delay
IEEE Transactions on Neural Networks
Technical communique: Reciprocally convex approach to stability of systems with time-varying delays
Automatica (Journal of IFAC)
Further results on delay-distribution-dependent robust stability criteria for delayed systems
International Journal of Automation and Computing
Stability analysis of discrete-time systems with additive time-varying delays
International Journal of Automation and Computing
International Journal of Automation and Computing
Stability analysis of discrete-time Lur'e systems
Automatica (Journal of IFAC)
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In this paper, through constructing some novel Lyapunov-Krasovskii functional (LKF) terms and using some effective techniques, two sufficient conditions are derived to guarantee a class of discrete-time time-delay systems with distributed delay to be asymptotically and robustly stable, in which the linear fractional uncertainties are involved and the information on the time-delays is fully utilized. By employing the improved reciprocal convex technique, some important terms can be reconsidered when estimating the time difference of LKF, and the criteria can be presented in terms of linear matrix inequalities (LMIs). Especially, these derived conditions heavily depend on the information of time-delay of addressed systems. Finally, three numerical examples demonstrate that our methods can reduce the conservatism more efficiently than some existing ones.