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Proceedings Paper

A novel method for block ambiguities of independent component analysis using previous demixing matrices
Author(s): Zhiyong Zhou; Mingxi Guo; Hao Duan; Shengyu Nie; Wei Zhao
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Paper Abstract

This manuscript deals with the permutation and scaling ambiguities inherent to an Independent Component Analysis (ICA) framework when continuously mixed signals are split in time and processed in a block-by-block manner. For each adjacent block, we choose the demixing matrix of the previous block as the initialization matrix for separating the subsequent block. By using the demixing matrices of the previous blocks, the separation process of the subsequent blocks is largely simplified, and the corresponding computational cost is thereby significantly reduced. Therefore, compared with previous similar methods, our proposed method is much more efficient in terms of computational speed, which is particularly striking when a large number of blocks is applied. We conducted simulations to validate the effectiveness of our proposed method.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003354 (29 August 2016); doi: 10.1117/12.2245309
Show Author Affiliations
Zhiyong Zhou, PLA Univ. of Science and Technology (China)
Mingxi Guo, PLA Univ. of Science and Technology (China)
Hao Duan, PLA Univ. of Science and Technology (China)
Shengyu Nie, PLA Univ. of Science and Technology (China)
Wei Zhao, PLA Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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