Title :
Blind identification and separation of convolutively mixed independent sources
Author :
Wang, Jun ; He, Zhenya
Author_Institution :
Dept. of Radio Eng., Southeast Univ., Nanjing, China
fDate :
7/1/1997 12:00:00 AM
Abstract :
A trispectra method for solving the m-input n-output (n≥m) wideband blind identification and signal separation problem with unknown number of sources m is presented. The method is universal in the sense that it does not impose any restriction on the probability distribution of the input signals provided that they are non-Gaussian. A criterion, which states a sufficient condition for identification and separation, has been proved. An algorithm is also developed based on the criterion, whose efficiency is verified by the simulations.
Keywords :
convolution; identification; probability; signal detection; spectral analysis; blind identification; convolutively mixed independent sources; m-input n-output problem; probability distribution; signal separation problem; trispectra method; Finite impulse response filter; MIMO; Maximum likelihood estimation; Probability distribution; Sensor phenomena and characterization; Signal processing algorithms; Source separation; Speech enhancement; Sufficient conditions; Wideband;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on