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Full-Text Articles in Engineering
A Delay-Dependent Approach To Robust Stability For Uncertain Hybrid Bidirectional Associative Memory Neural Networks With Time-Varying Delays, Chien-Yu Lu, Koan-Yuh Chang, Hsun-Heng Tsai, Wen-Jer Chang
A Delay-Dependent Approach To Robust Stability For Uncertain Hybrid Bidirectional Associative Memory Neural Networks With Time-Varying Delays, Chien-Yu Lu, Koan-Yuh Chang, Hsun-Heng Tsai, Wen-Jer Chang
Journal of Marine Science and Technology
This paper performs a global robust stability analysis of a particular class of hybrid bidirectional associative memory time-varying delayed neural network with norm-bounded timevarying parameter uncertainties. The activation functions are assumed to be globally Lipschitz continuous. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing relaxation matrices which, when chosen properly, produce a less conservative result. Two numerical examples are given to illustrate the significant improvement obtained in the conservativeness of the delay bound.
A Delay-Dependent Approach To Robust Stability For Uncertain Stochastic Neural Networks With Time-Varying Delay, Chien-Yu Lu, Chin-Wen Liao, Koan-Yuh Chang, Wen-Jer Chang
A Delay-Dependent Approach To Robust Stability For Uncertain Stochastic Neural Networks With Time-Varying Delay, Chien-Yu Lu, Chin-Wen Liao, Koan-Yuh Chang, Wen-Jer Chang
Journal of Marine Science and Technology
This paper investigates the global delay-dependent robust stability in the mean square for uncertain stochastic neural networks with time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. Based on a linear matrix inequality approach, globally delay-dependent robust stability criterion is derived by introducing some relaxation matrices which, when chosen properly, lead to a less conservative result. Two numerical examples are given to illustrate the effectiveness of the method.