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This study aims to develop an intelligent algorithm by integrating robust independent component analysis (RobustICA) and support vector machines (SVMs). According to different characteristics of source signals including real or complex, super-Gaussian or sub-Gaussian and pollution of signal noise, a new method for fault detection that uses RobustICA based on kurtosis is put forward in this paper....
Traditional blind separation methods perform well when the number of source signals is constant, but in practice, the number is usually time-varying. In this case, traditonal methods can hardly achieve separation. In this paper, a method is presented to deal with the problem of blind separation for chaotic signals in a dynamic environment. This paper first establishes dynamic system model that based...
We propose a new algorithm, called the central difference filter - Kalman filter (CDF-KF) for conditionally linear Gaussian state space models. The linear state equation is firstly inserted into the measurement equation, and the CDF is applied to the new measurement and the nonlinear state equations to estimate the nonlinear states, where after the estimated means of the nonlinear states are substituted...
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