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

delete2008-02-01
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PRE
AI
S
Shih‐Hsuan Chiu *
C
Chuan‐Pin Lu
D
Dien‐Chi Wu
C
Che‐Yen Wen
DOI:10.1016/j.patrec.2007.10.014delete
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Abstract

Abstract

En 中文
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. 1024 x 1024 images). (c) 2007 Elsevier B.V. All rights reserved.
Keywords:
independent component analysis
FastICA
data reduction

Journal

Pattern Recognition Letters cover
Pattern Recognition Letters
IF:
3.3
Papers:
7.9K
Citations:
1.6W

Organization

N
national taiwan university of science & technology
Scholars:
8.8K
Papers: 8.7K
Citations: 9