Code-length-based universal extraction for blind signal separation

Abstract

We propose a blind signal separation algorithm (CLUE) that uses the sum of the individual code lengths of the extracted signals as a measure of the separation performance. The new technique combines a widely-available universal data compression routine with any single-parameter search procedure. Unlike previous approaches, the proposed method is model-free and does not rely on the moment values of the signals for its separation performance. An example shows the algorithm's efficiency in separating mixtures of image, audio, and text data.