Established in 2005 under support of MŠMT ČR (project 1M0572)

Publications

A Fast Asymptotically Efficient Algorithm for Blind Separation of a Linear Mixture of Block-Wise Stationary Autoregressive Processes

Typ:
Conference paper
Authors:
Proceedings name:
Proceedings of 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher:
IEEE
Serie:
Taipei
Year:
2009
ISBN:
978-1-4244-2354-5
Keywords:
Approximate joint diagonalization, blind source separation,,
Anotation:
We propose a novel blind source separation algorithm called Block AutoRegressive Blind Identification (BARBI). The algorithm is asymptotically efficient in separation of instantaneous linear mixtures of blockwise stationary Gaussian autoregressive processes. A novel closed-form formula is derived for a Cramer Rao lower bound on elements of the corresponding Interference-to-Signal Ratio (ISR) matrix. This theoretical ISR matrix can serve as an estimate of the separation performance on the particular data. In simulations, the algorithm is shown to be applicable in blind separation of a linear mixture of speech signals.
 
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