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One-Unit Fixed-Point Complex-valued ICA-R Algorithm Using Magnitude Information |
Li Jing Lin Qiu-hua |
(School of Electronic and Information Engineering, Dalian University of Technology, Dalian 116023, China) |
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Abstract Independent Component Analysis with Reference (ICA-R) extracts only desired signals by incorporating prior information as reference signals. It can provide output signals with definite order and improved performance. However, no ICA-R algorithm in complex domain has been reported till now. Motivated by the fact that the magnitude information of a complex-valued signal is readily obtained, this paper proposes a fixed-point complex-valued ICA-R algorithm to extract a desired signal by utilizing its magnitude information in the framework of constrained ICA. Specifically, the complex ICA-R is formulated as maximizing the contrast function of a blind complex fastICA algorithm under an inequality constraint corresponding to the magnitude information, the augmented Lagrangian function and Kuhn-Tucker conditions are then used to derive the fixed-point algorithm. The results of computer simulations and performance analysis demonstrate that the complex-valued ICA-R algorithm outperforms the blind complex fastICA algorithm by virtue of incorporation of magnitude information.
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Received: 20 April 2007
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Corresponding Authors:
Li Jing
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