Fast independent component analysis algorithm for quaternion valued signals.
An extension of the fast independent component analysis algorithm is proposed for the blind separation of both Q-proper and Q-improper quaternion-valued signals. This is achieved by maximizing a negentropy-based cost function, and is derived rigorously using the recently developed HR 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.
Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK. soroush.javidi02@imperial.ac.uk
Soroush
S
Javidi
Clive Cheong
CC
Took
Danilo P
DP
Mandic
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D012815:Signal Processing, Computer-Assisted