Code-length-based universal extraction for blind signal separation

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