W. Qin

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This paper deals with the parameter and state estimation problem for the Lipschitz nonlinear systems. First, a nonlinear adaptive observer for a class of Lipschitz nonlinear systems is designed, and based on LMI the stability conditions are derived. Then for a class of nonlinear system, the new sufficient conditions are derived, which ensure the convergence(More)
Radio Frequency Identification (RFID) technologies provide automatic and accurate object data capturing capability and enable real-time object visibility and trace-ability. Potential benefits have been widely reported for improving manufacturing shop-floor management. However, reports on how such potentials come true in real-life shop-floor daily operations(More)
The quality assessment of fusion images is of fundamental importance for most image fusion applications. Piella proposes a quality metric for image fusion based on structural similarity but it has been proved not so good in some cases. In this paper we present a novel objective fusion image quality index which is also very easy to calculate and applicable(More)
The aim of the present study is to observe the receptor kinetics property of long-term potentiation (LTP) of excitatory postsynaptic potential (EPSP) in spinal cord motoneurons (MNs) by descending activation. The intracellular recording techniques were conducted in spinal cord MNs of neonatal rats aged 8-14 days. The changes of EPSP induced by ipsilateral(More)
Outlier mining is an important branch of data mining and has attracted much attention recently. The density-based method LOF is widely used in application. However, the complexity of the method is quadratic to size of the dataset, and it is very sensitive to its parameters MinPts. In this paper, we propose a new outlier detection method based on Voronoi(More)
—Outlier detection has wide application for financial surveillance. The Traditional outlier detection method is based on statistical models, such as ARMA and ARCH, which require special hypotheses. The statistical models are inappropriate to apply to complex financial data, such as high frequency data. This paper introduces a new data mining method to(More)
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