First International Workshop on Independent Component Analysis and Signal Separation (ICA'99)

REAL WORLD BLIND separation OF CONVOLVED NON-STATIONARY
SIGNALS

M. Kawamoto1, A. k. Barros1, A. Mansour 1,  K. Matsuoka2 and N. Ohnishi 3
l.Bio-mimetic Control Research center, RIKEN, 2271-130 Anagahora, Shimoshidami, Moriyxma-ku, Nagoya, 463-0003, Japan

 2. Department of Control Engineering, Kyushu Institute of Technology (Japan),
3. Graduate School of Engineering, Nagoya University (Japan)


abstract:
In this paper, a method of blind separation for convolved non-stationary signals
 (e.g., speech signals and music) is presented. Our method achieves blind separation
  by forcing mixed signals to uncorrelate with each other. The validity of the
  proposed method has been confirmed by a computer simulation and an experiment
  in an anechoic room (7). In this paper, we apply our method to an experiment
  which extracts two source signals from their mixture observed in a normal room.
  The experiment is implemented in a noisy environment. Moreover, we test our algorithm using the
data obtained from Computational Neurobiology lab's Blind Source Separation Web Page.