Title :
Blind source separation of audio signals using improved ICA method
Author :
Sattar, F. ; Siyal, M.Y. ; Wee, L.C. ; Yen, L.C.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fDate :
6/23/1905 12:00:00 AM
Abstract :
Blind source separation (BSS) of independent sources from their convolutive mixtures is a problem in many real-world multi-sensor applications. In this paper, we propose an improved BSS method for audio signals based on ICA (independent component analysis) technique. It is performed by implementing non-causal filters instead of causal filters within the feedback network of the ICA based BSS method. It reduces the required length of the unmixing filters considerably as well as providing better results and faster convergence compared to the case with the conventional causal filters. The proposed method has been simulated and compared for real world audio signals
Keywords :
audio signal processing; convolution; filtering theory; statistical analysis; ICA method; audio signals; blind source separation; convergence; convolutive mixtures; independent component analysis; independent sources; multi-sensor applications; noncausal filters; Blind source separation; Feedback; Filters; Higher order statistics; Independent component analysis; Iterative algorithms; Microphones; Signal analysis; Signal processing; Source separation;
Conference_Titel :
Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
Print_ISBN :
0-7803-7011-2
DOI :
10.1109/SSP.2001.955320