Blind Separation for convolutive Mixtures of Non-stationary Signals
     
Mitsuru KAWAMOTO 1 , Allan Kardec BARROS 1 , Ali MANSOUR ,
   
Kiyotoshi MATSUOKA 2 . and Noboru OHNISHI 1,3
l . Bio-Mimetic Control Research Center, RIKEN,
2271-130 Anagahora, Shimoshidnmi, Moriyamn-ku, Nagoya, 463. Japan
   
2. Department of Control Engineering, Kyushu Institute of Technology.
3. Graduate School of Engineering, Nagoya University

Abstract-This paper proposes a method of ''blind
separation'' which extracts non-stationary signals (e.g.,
speech signals, music) from their convolutive mixtures.
The function is acquired by modifying a network's
parameters so that a cost function takes the minimum at
any time. the cost function is the one introduced by
Matsuoka et al.   The learning rule is derived from
the natural gradient   minimization of the cost
function. The validity of the proposed method is
confirmed by computer simulation.