Jason Sheng Hong Tsai

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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)
An effective and efficient successful-parent-selecting framework is proposed to improve the performance of differential evolution by providing alternative for the selection of parents during mutation and crossover. The proposed method adapts the selection of parents by storing successful solutions into an archive, and the parents are selected from the(More)
A constraint-activated differential evolution is proposed to solve constrained min–max optimization problems in this paper. To provide theoretical understanding for these problems, their global optima are specified in the proposed definitions. Based on the definition, we propose theorems to prove that a min–max algorithm can be used to solve a max–min(More)
Based on the modified state-space self-tuning control (STC), a novel low-order tuner via the modified observer/Kalman filter identification (OKID) is proposed for stochastic fractionalorder chaotic systems. The OKID method is a time-domain technique that identifies a discrete input-output map by using known input-output sampled data in the general(More)