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Analysis of source separation algorithms in industrial acoustic environments

dc.contributor.authorLozano, Clevis
dc.contributor.authorGómez, Andrés
dc.contributor.authorChacón-Rodríguez, Alfonso
dc.contributor.authorMerchán, Fernando
dc.contributor.authorJulián, Pedro
dc.date.accessioned2017-04-05T17:34:55Z
dc.date.available2017-04-05T17:34:55Z
dc.date.issued2015
dc.identifier.citationhttps://www.scopus.com/inward/record.url?eid=2-s2.0-84945156117&partnerID=40&md5=72998182186ff5845045de39e1c40ab7es
dc.identifier.isbn978-147998332-2
dc.identifier.urihttps://hdl.handle.net/2238/6943
dc.description.abstractThis paper shows the results from the computation cost evaluation of three blind source separation algorithms. The algorithms tested were: FastICA, Adaptive Algorithm Based on Natural Gradient, and Adaptive EASI Based on Relative Gradient. The algorithms were chosen for their relative simplicity, and taking into account their hardware implementation feasibility, either on a FPGA or an ASIC, as part of a system for acoustic localization of mobile agents in industrial environments.es
dc.language.isoenges
dc.publisherInstitute of Electrical and Electronics Engineers Inc.es
dc.rightsAttribution-NonCommercial 3.0 Costa Rica*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/cr/*
dc.sourceC. Lozano, A. Gómez, A. Chacón-Rodríguez, F. Merchán, & P. Julian. (2015). Analysis of source separation algorithms in industrial acoustic environments. Paper presented at the 2015 IEEE 6th Latin American Symposium on Circuits & Systems (LASCAS), 1-4. doi:10.1109/LASCAS.2015.7250482
dc.subjectAlgoritmoses
dc.subjectHardwarees
dc.subjectResearch Subject Categories::TECHNOLOGY::Information technology::Computer science::Computer sciencees
dc.titleAnalysis of source separation algorithms in industrial acoustic environmentses
dc.typeinfo:eu-repo/semantics/conferenceObjectes


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