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タイトル: Analysis of signal separation and signal distortion in feedforward and feedback blind source separation based on source spectra
著者: Horita, Akihide
Nakayama, Kenji link image
Hirano, Akihiro link image link image
Dejima, Yasuhiro
中山, 謙二
平野, 晃宏
発行日: 2005年 8月
出版社(者): IEEE(Institute of Electrical and Electronics Engineers)
雑誌名: Proceedings of the International Joint Conference on Neural Networks
巻: 2
開始ページ: 1257
終了ページ: 1262
抄録: Source separation and signal distortion in three kinds of BSSs with convolutive mixture are analyzed. They include a feedforward BSS, trained in the time domain and in the frequency domain, and a feedback BSS, trained in the time domain. First, an evaluation measure of signal distortion is discussed. Second, conditions for source separation and distortion free are derived. Based on these conditions, source separation and signal distortion are analyzed. The feedforward BSS has some degree of freedom, and the output spectrum can be changed. The feedforward BSS, trained in the frequency domain, has weighting effect, which can suppress signal distortion. This weighting is, however, effective only when the source spectra are similar to each other. Since, the feedforward BSS, trained in the time domain, does not have any constraints on signal distortion free, its output signals can be easily distorted. A new learning algorithm with a distortion free constraint is proposed. On the other hand, the feedback BSS can satisfy both source separation and distortion free conditions simultaneously. Simulation results support the theoretical analysis. © 2005 IEEE.
DOI: 10.1109/IJCNN.2005.1556034
URI: http://hdl.handle.net/2297/6815
資料種別: Conference Paper
版表示: publisher

このアイテムを引用あるいはリンクする場合は次の識別子を使用してください。 http://hdl.handle.net/2297/6815



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