Independent Component Analysis of Complex Valued Signals Based on First-order Statistics

This paper proposes a novel method based on first-order statistics, aims to solve the problem of the independent component extraction of complex valued signals in instantaneous linear mixtures. Single-step and iterative algorithms are proposed and discussed under the engineering practice. Theoretica...

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Veröffentlicht in:Radioengineering 2013-12, Vol.22 (4), p.1194-1201
Hauptverfasser: P.C. Xu, Y.H. Shen, H. Li, J.G. Wang, K. Wu
Format: Artikel
Sprache:eng
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Zusammenfassung:This paper proposes a novel method based on first-order statistics, aims to solve the problem of the independent component extraction of complex valued signals in instantaneous linear mixtures. Single-step and iterative algorithms are proposed and discussed under the engineering practice. Theoretical performance analysis about asymptotic interference-to-signal ratio (ISR) and probability of correct support estimation (PCE) are accomplished. Simulation examples validate the theoretic analysis, and demonstrate that the single-step algorithm is extremely effective. Moreover, the iterative algorithm is more efficient than complex FastICA under certain circumstances.
ISSN:1210-2512