Independent component analysis based on marginal density estimation using weighted Parzen windows - Wu, Jiann-Ming; Chen, Meng-Hong; Lin, Zheng-Han (Neural networks, 2008)
Keywords: Algorithms; Applied sciences; Biological and medical sciences; Blind source separation; Coding, codes; Computer Simulation; Computerized, statistical medical data processing and models in biomedicine; Density estimation; Detection, estimation, filtering, equalization, prediction; Electrocardiography - methods; Electroencephalography - methods; Entropy; Evoked Potentials - physiology; Exact sciences and technology; Humans; Independent factor analysis; Information, signal and communications theory; Kullback–Leibler divergence; Mean field annealing; Medical management aid. Diagnosis aid; Medical sciences; Miscellaneous; Nonlinear Dynamics; Potts encoding; Principal Component Analysis; Signal and communications theory; Signal processing; Signal Processing, Computer-Assisted; Signal, noise; Statistics, Nonparametric; Telecommunications and information theory; Weighted Parzen window; Density estimation; Kullback–Leibler divergence; Mean field annealing; Potts encoding; Blind source separation; Entropy; Weighted Parzen window; Independent factor analysis; Signal mixing; Divergence; Density measurement; Signal estimation; Kullback-Leibler divergence; Gradient descent; Accuracy; Multidimensional analysis; Coding; Facies; Electrocardiography; Work; Gradient method; Annealing; Independent component analysis; Interactive system; Descent method; Observation; Signal processing; Numerical simulation; Reliability; EM algorithm; Event evoked potential