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Aiming at the weaknesses of PS-classifier, it is easily trapped into locally optimal solution and slow convergence velocity when it deals with the complex problems, an improved quantum-behaved particle swarm classifier has been proposed in the paper. Firstly, It introduce the weighted mean best position to improve the performance of QPSO (quantum-behaved particle swarm), and use a novel Michigan rule...
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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