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Analysis of signal separation and signal distortion in feedforward and feedback blind source separation based on source spectra
http://hdl.handle.net/2297/18169
http://hdl.handle.net/2297/181698a2fb17e-916c-4e7d-9fb3-596098cb3e87
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
TE-PR-NAKAYAMA-K-1257.pdf (258.9 kB)
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| Item type | 会議発表論文 / Conference Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2017-10-03 | |||||
| タイトル | ||||||
| タイトル | Analysis of signal separation and signal distortion in feedforward and feedback blind source separation based on source spectra | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
| 資源タイプ | conference paper | |||||
| 著者 |
Horita, Akihide
× Horita, Akihide× Nakayama, Kenji× Hirano, Akihiro× Dejima, Yasuhiro |
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| 提供者所属 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | 金沢大学理工研究域 電子情報学系 | |||||
| 書誌情報 |
Proceedings of the International Joint Conference on Neural Networks 2, Montreal p. 1257-1262, 発行日 2005-07-01 |
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| DOI | ||||||
| 関連タイプ | isIdenticalTo | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.1109/IJCNN.2005.1556034 | |||||
| 出版者 | ||||||
| 出版者 | IEEE = Institute of Electrical and Electronics Engineers | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | 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. | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
| シリーズ | ||||||
| 関連名称 | IJCNN2005 | |||||
| シリーズ | ||||||
| 関連名称 | 1556034 | |||||
