Augmented complex matrix factorisation

A novel framework for the factorisation of complex-valued data is derived using recent developments in complex statistics. Unlike existing factorisation tools the algorithms can cater for noncircularity of the input - a necessary feature in applications for modelling real-world data. It is furthermore shown how the framework can be constrained to incorporate nonnegativity,helping generate results which allow a more realistic interpretation. Simulations illustrate the usefulness and enhanced accuracy for modelling synthetic data and a mixture of acoustic stimuli.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: David Looney, Danilo P. Mandic
• Keywords: Acoustic Stimuli, Factorisation Tools, ICASSP 2011, Real-world Data, Signal Processing