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Fast Independent Component Analysis Algorithm for Quaternion Valued Signals

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3 Author(s)
Soroush Javidi ; Department of Electrical and Electronic Engineering, Imperial College London, London, U.K. ; Clive Cheong Took ; Danilo P. Mandic

An extension of the fast independent component analysis algorithm is proposed for the blind separation of both BBQ-proper and BBQ-improper quaternion-valued signals. This is achieved by maximizing a negentropy-based cost function, and is derived rigorously using the recently developed mbiBBHBBR calculus in order to implement Newton optimization in the augmented quaternion statistics framework. It is shown that the use of augmented statistics and the associated widely linear modeling provides theoretical and practical advantages when dealing with general quaternion signals with noncircular (rotation-dependent) distributions. Simulations using both benchmark and real-world quaternion-valued signals support the approach.

Published in:

IEEE Transactions on Neural Networks  (Volume:22 ,  Issue: 12 )