A fast asymptotically efficient algorithm for blind separation of a linear mixture of block-wise stationary autoregressive proce

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 Cram´er 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.

• Type: Conference
• Year: 2009
• Where: ICASSP
• Authors: Petr Tichavský, Arie Yeredor, Zbynek Koldovský
• Keywords: AutoRegressive Blind Identification, ICASSP 2009, Linear Mixture, Signal Processing, Source Separation Algorithm