An independent component analysis algorithm through solving gradient equation combined with kernel density estimation |
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Authors: | Yun-feng Xue Yu-jia Wang Jie Yang |
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Institution: | (1) Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, 200240, China;(2) Department of Automation, Shanghai Jiaotong University, Shanghai, 200240, China |
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Abstract: | A new algorithm for linear instantaneous independent component analysis is proposed based on max-imizing the log-likelihood contrast function which can be changed into a gradient equation. An iterative method is introduced to solve this equation efficiently. The unknown probability density functions as well as their first and second derivatives in the gradient equation are estimated by kernel density method. Computer simulations on artificially generated signals and gray scale natural scene images confirm the efficiency and accuracy of the proposed algorithm. |
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Keywords: | independent component analysis blind source separation gradient method kernel density estimation |
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