Chin-Wen Liao

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This paper deals with the problem of passivity analysis for neural networks with time-varying delay, which is subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. Delay-dependent passivity condition is proposed by using the free-weighting matrix approach. These(More)
The state estimation problem for discrete-time recurrent neural networks with both interval discrete and infinite-distributed time-varying delays is studied in this paper, where interval discrete time-varying delay is in a given range. The activation functions are assumed to be globally Lipschitz continuous. A delay-dependent condition for the existence of(More)
This paper deals with the problem of state estimation for discrete stochastic recurrent neural network with interval time-delays. The activation functions are assumed to be globally Lipschitz continuous. Attention is focused on the design of a state estimator which ensures the global stability of the estimation error dynamics. A delay-dependent condition(More)
This paper deals with the problem of Passivity analysis for neural networks with multiple time-varying delays subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. New passivity conditions are proposed by using Lyapunov-Krasovskii function-als and the(More)
In this study, we examined the development of industry-oriented safety degree curricula at a college level. Based on a review of literature on the practices and study of the development of safety curricula, we classified occupational safety and health curricula into the following three domains: safety engineering, health engineering, and safety and health(More)
This paper proposes a new method to detect transformer inside incipient fault current using transformer internal parameters to determine the inside structure of transformer at good condition or bad. A transformer model was established by Jiles– Atherton theory using measured voltage and current and the initial parameters which were found using Genetic(More)
This paper deals with the problem of delay-dependent robust H ∞ control for discrete-time recurrent neural networks (DRNNs) with norm-bounded parameter uncertainties and interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. For the robust stabilization problem, a state feedback controller is designed to(More)