A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices
This paper proposes a new algorithm to improve robustness, reliability and efficiency for blind signal separation with a different diagonal cumulant maximization criterion. It calculates a fraction of the fourth order cumulant set and avoids the eigenmatrix decomposition to considerably reduce the s...
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| Other Authors: | |
| Format: | Conference Paper |
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Australian Institute of Physics
2005
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| Online Access: | http://hdl.handle.net/20.500.11937/5080 |
| _version_ | 1848744696439898112 |
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| author | Liu, Xianhua Randall, R. |
| author2 | Hans-A. Bachor |
| author_facet | Hans-A. Bachor Liu, Xianhua Randall, R. |
| author_sort | Liu, Xianhua |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper proposes a new algorithm to improve robustness, reliability and efficiency for blind signal separation with a different diagonal cumulant maximization criterion. It calculates a fraction of the fourth order cumulant set and avoids the eigenmatrix decomposition to considerably reduce the separation cost for large-scale problems. Experimental separation shows that the new algorithm is robust, reliable and efficient for both large and small-scale separation problems, thus has combined merits of the well-known JADE and Fast ICA algorithms. Mixed music and speech signal separation is presented in this paper. |
| first_indexed | 2025-11-14T06:05:34Z |
| format | Conference Paper |
| id | curtin-20.500.11937-5080 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:05:34Z |
| publishDate | 2005 |
| publisher | Australian Institute of Physics |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-50802022-10-11T07:36:51Z A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices Liu, Xianhua Randall, R. Hans-A. Bachor Massimiliano Colla Independent component analysis Blind source separation fourth order cumulant matrix diagonalization This paper proposes a new algorithm to improve robustness, reliability and efficiency for blind signal separation with a different diagonal cumulant maximization criterion. It calculates a fraction of the fourth order cumulant set and avoids the eigenmatrix decomposition to considerably reduce the separation cost for large-scale problems. Experimental separation shows that the new algorithm is robust, reliable and efficient for both large and small-scale separation problems, thus has combined merits of the well-known JADE and Fast ICA algorithms. Mixed music and speech signal separation is presented in this paper. 2005 Conference Paper http://hdl.handle.net/20.500.11937/5080 Australian Institute of Physics restricted |
| spellingShingle | Independent component analysis Blind source separation fourth order cumulant matrix diagonalization Liu, Xianhua Randall, R. A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices |
| title | A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices |
| title_full | A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices |
| title_fullStr | A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices |
| title_full_unstemmed | A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices |
| title_short | A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices |
| title_sort | new independent component analysis algorithm: joint approximate diagonalization of simplified cumulant matrices |
| topic | Independent component analysis Blind source separation fourth order cumulant matrix diagonalization |
| url | http://hdl.handle.net/20.500.11937/5080 |