説明
<jats:p>Independent component analysis (ICA) is a widely-used blind source separation technique. ICA has been applied to many applications. ICA is usually utilized as a black box, without understanding its internal details. Therefore, in this paper, the basics of ICA are provided to show how it works to serve as a comprehensive source for researchers who are interested in this field. This paper starts by introducing the definition and underlying principles of ICA. Additionally, different numerical examples in a step-by-step approach are demonstrated to explain the preprocessing steps of ICA and the mixing and unmixing processes in ICA. Moreover, different ICA algorithms, challenges, and applications are presented.</jats:p>
収録刊行物
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- Applied Computing and Informatics
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Applied Computing and Informatics 17 (2), 222-249, 2020-08-04
Emerald
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詳細情報 詳細情報について
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- CRID
- 1360579818458635136
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- ISSN
- 22108327
- 26341964
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- Web Site
- https://api.elsevier.com/content/article/PII:S2210832718301819?httpAccept=text/xml
- https://api.elsevier.com/content/article/PII:S2210832718301819?httpAccept=text/plain
- https://www.emerald.com/insight/content/doi/10.1016/j.aci.2018.08.006/full/xml
- https://www.emerald.com/insight/content/doi/10.1016/j.aci.2018.08.006/full/html
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- データソース種別
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