Title :
A learning algorithm with distortion free constraint and comparative study for feedforward and feedback BSS
Author :
Horita, Akihide ; Nakayama, Kenji ; Hirano, Akihiro ; Dejima, Yasuhiro
Author_Institution :
Grad. Sch. of Natural Sci. & Technol., Kanazawa Univ. Kakuma-machi, Kanazawa, Japan
Abstract :
Source separation and signal distortion are theoretically analyzed for the FF-BSS systems implemented in both the time and frequency domains and the FB-BSS system. The FF-BSS systems have some degree of freedom, and cause some signal distortion. The FB-BSS has a unique solution for complete separation and signal distortion free. Next, the condition for complete separation and signal distortion free is derived for the FF-BSS systems. This condition is applied to the learning algorithms. Computer simulations by using speech signals are carried out for the conventional methods and the new learning algorithms employing the proposed distortion free constraint. The proposed method can drastically suppress signal distortion, while maintaining high separation performance. The FB-BSS system also demonstrates good performances. The FF-BSS systems and the FB-BSS system are compared based on the transmission time difference in the mixing process. Location of the signal sources and the sensors are rather limited in the FBBSS system.
Keywords :
acoustic distortion; acoustic signal processing; blind source separation; feedback; feedforward; frequency-domain analysis; learning (artificial intelligence); speech processing; time-domain analysis; FB-BSS system; FF-BSS systems; blind source separation; distortion free constraint; feedback BSS system; feedforward BSS system; frequency domains; learning algorithm; mixing process; sensors; signal distortion; signal sources; speech signals; time domains; transmission time difference; Abstracts; Artificial neural networks; Distortion; Source separation;
Conference_Titel :
Signal Processing Conference, 2006 14th European
Conference_Location :
Florence
