Zixin Liu

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The robust stability of uncertain discrete-time recurrent neural networks with time-varying delay is investigated. By decomposing some connection weight matrices, new Lyapunov-Krasovskii functionals are constructed, and serial new improved stability criteria are derived. These criteria are formulated in the forms of linear matrix inequalities LMIs. Compared(More)
Circulating tumor cells (CTCs) originate from tumor tissues and are associated with cancer prognosis. However, existing technologies for CTC detection are limited owing to a lack of specific or accurate biomarkers. Here, we developed a new method for CTC detection based on the karyoplasmic ratio, without biomarkers. Consecutive patients with liver cancer or(More)
Aimed at the ordering problem of fuzzy sets, an approximate fuzzy set is obtained by rough fuzzy sets. It has good geometric meaning and simple operation, which makes it a good approximation method to research fuzzy sets. Since rough fuzzy number keeping weak partial order, by this property, better research results are gained on ordering of fuzzy sets. This(More)
—This paper studies the mean square exponential synchronization problem of a class of stochastic neutral type chaotic neural networks with mixed delay. On the Basis of Lyapunov stability theory, some sufficient conditions ensuring the mean square exponential synchronization of two identical chaotic neural networks are obtained by using stochastic analysis(More)