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Fast and Versatile Blind Separation of Diverse Sounds Using Closed-Form Estimation of Probability Density Functions of Sources

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dc.contributor.author Hiroshi Saruwatari ja
dc.contributor.author Yu Takahashi ja
dc.contributor.author Kentaro Tachibana ja
dc.contributor.author Yoshimitsu Mori ja
dc.contributor.author Shigeki Miyabe ja
dc.contributor.author Kiyohiro Shikano ja
dc.contributor.author Akira Tanaka ja
dc.date.accessioned 2012-08-22T07:58:40Z
dc.date.available 2012-08-22T07:58:40Z
dc.date.issued 2009-12 ja
dc.identifier.isbn 9781424451807
dc.identifier.uri http://hdl.handle.net/10061/7929
dc.description CAMSAP2009: the 3rd International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, December 13-16, 2009, Aruba, Dutch Antilles. ja
dc.description.abstract In this paper, we propose a fast and versatile blind source separation including closed-form estimation of sources' probability density functions (PDFs), where the ICA's activation function is automatically adapted to various noise conditions. In the proposed method, closed-form second-order ICA and closed-form PDF estimation are introduced as a computational-cost-efficient preprocessing to extract sources' PDFs. Compared with various type of conventional ICAs, e.g., fixed activation-function type and ML-based type, our proposed algorithm can give a faster and higher convergence. Experimental assessment reveals that the proposed method is versatile for handling non-speech sound sources. ja
dc.language.iso en ja
dc.publisher IEEE ja
dc.rights Copyright 2009 IEEE ja
dc.title Fast and Versatile Blind Separation of Diverse Sounds Using Closed-Form Estimation of Probability Density Functions of Sources ja
dc.type.nii Conference Paper ja
dc.textversion Publisher ja
dc.identifier.spage 249 ja
dc.identifier.epage 252 ja
dc.relation.doi 10.1109/CAMSAP.2009.5413289 ja


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