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A novel method based on Hilbert Huang Transform (HHT) for analyzing the non-linear and non-stationary shock signal is presented. The frequency components of the shock signal are complicated, Empirical Mode Decomposition (EMD) can decompose the signal into Intrinsic Mode Functions (IMFs), and after Hilbert transform the instantaneous frequency of each IMF is obtained, then can get the physical meaning...
Fast changing knowledge on the Internet can be acquired more efficiently with the help of automatic document summarization and updating techniques. This paper described a novel approach for multi-document update summarization. The best summary is defined to be the one which has the minimum information distance to the entire document set. The best update summary has the minimum conditional information...
A novel signal source separation method is introduced for analysis of intrinsic Optical Imaging (OI) and functional Magnetic Resonance Imaging (fMRI) data. This method is based on the fact that all real interesting signals are autocorrelated spatially as well as temporally. Many signal source separation algorithms which using autocorrelation or other structure information of the interesting signals,...
This paper presents a robust speaker identification approach basing on kernel principle component analysis (KPCA) and probabilistic neural network (PNN). KPCA is exploited to reduce the dimension of input vector and to denoise speech signal by extracting the nonlinear principle components of the feature vector. The extracted principle components are utilized as the input feature vector of the classifier...
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