Conference proceeding
A SEMI-BLIND EM ALGORITHM FOR OVERCOMPLETE ICA
2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, pp 1733-1736
01 Jan 2009
Abstract
Overcomplete independent component analysis (ICA) is a challenge of ICA to estimate more sources from less mixtures. The statistical properties of the sources such as sparsity are often assumed to solve the problem. Other available information about the sources such as waveform, however, is scarcely used. Motivated by the fact that semi-blind ICA in complete case can improve the potential of ICA by incorporating source information, this paper proposes a semi-blind algorithm for overcomplete ICA by explicitly utilizing waveform information about some sources. An approximate expectation-maximization (EM) algorithm is explored to provide normal cost function of the semi-blind algorithm while the prior information is utilized to form an extended one. Computer simulations results demonstrate that the proposed algorithm has much improved performance in SNR, convergence speed, and elimination of order ambiguity compared to the original EM algorithm.
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Details
- Title
- A SEMI-BLIND EM ALGORITHM FOR OVERCOMPLETE ICA
- Creators
- Qiuhua Lin - Dalian University of TechnologyNing Xu - Dalian University of TechnologyHualou Liang - Supreme Council Of HealthIEEE
- Publication Details
- 2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, pp 1733-1736
- Series
- International Conference on Acoustics Speech and Signal Processing ICASSP
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- 60402013 / National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC) 20062174 / Liaoning Province Natural Science Foundation of China; Natural Science Foundation of Liaoning Province
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000268919200434
- Scopus ID
- 2-s2.0-70349218084
- Other Identifier
- 991019320712804721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Acoustics
- Engineering, Electrical & Electronic