Orthogonal approach to independent component analysis using quaternionic factorization

Orthogonal approach to independent component analysis using quaternionic factorization

Abstract Independent component analysis (ICA) is a popular technique for demixing multichannel data. The performance of a typical ICA algorithm strongly depends on the presence of additive noise, the actual distribution of source signals, and the estimated number of non-Gaussian components. Often, a...

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Bibliographic Details
Main Author: Adam Borowicz
Format: Article
Language:English
Published: SpringerOpen 2020-09-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
BSS
ICA
Jacobi rotations
Negentropy
Quaternions
Online Access:http://link.springer.com/article/10.1186/s13634-020-00697-0

Internet

http://link.springer.com/article/10.1186/s13634-020-00697-0

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