A histogram based data-reducing algorithm for the fixed-point independent component analysis

Authors:
Shih-Hsuan Chiu;Chuan-Pin Lu;Dien-Chi Wu;Che-Yen Wen
Affiliations:
Department of Polymer Engineering, National Taiwan University of Science and Technology, 43, Section 4, Keelung Road, Taipei 10672, Taiwan;Department of Information Technology, Meiho Institute of Technology, 23, Ping Kuang Road, Nei Pu, Pingtung, Taiwan;Department of Polymer Engineering, National Taiwan University of Science and Technology, 43, Section 4, Keelung Road, Taipei 10672, Taiwan;Department of Forensic Science, Central Police University, 56, Shu Ren Road, Kuei Shan, Taoyuan, Taiwan
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

This paper proposes a histogram based data-reducing algorithm for improving the performance of the fixed-point independent component analysis (FastICA). This data-reducing independent component analysis (DR-FastICA) is based upon two statistical criteria to keep the histogram contour of processed data. This algorithm uses two steps (a coarse step for data sampling and a fine one for data tuning) to improve the performance of FastICA. Experimental results show that the proposed algorithm can reduce the computation time and implementation memory needed for executing FastICA, especially for large amounts of data (e.g. 1024x1024 images).