Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/20398
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dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorLi, Zen_US
dc.creatorYiu, KFCen_US
dc.date.accessioned2015-10-13T08:26:43Z-
dc.date.available2015-10-13T08:26:43Z-
dc.identifier.issn0952-1976en_US
dc.identifier.urihttp://hdl.handle.net/10397/20398-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2015 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Li, Z., & Yiu, K. F. C. (2016). Beamformer configuration design in reverberant environments. Engineering Applications of Artificial Intelligence, 47, 81-87 is available at https://doi.org/10.1016/j.engappai.2015.04.015.en_US
dc.subjectHybrid descent methoden_US
dc.subjectLCMV beamformingen_US
dc.subjectMicrophone array configurationen_US
dc.subjectReverberationen_US
dc.titleBeamformer configuration design in reverberant environmentsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1016/j.engappai.2015.04.015en_US
dcterms.abstractMany speech-related products rely on the deployment of microphone arrays and standard regular configurations are often used. In enhancing speech quality, the placement of microphones is indeed an important factor. Moreover, for indoor applications, the room acoustics further increases the difficulty. In this paper, these problems are addressed. First, we define the LCMV beamformer design problem using estimated room impulse responses with reverberation. Then, we study the performance limit on the filter length and formulate the configuration design problem. Finally, we employ a hybrid descent method with the genetic algorithm for solving the design problem. Numerical examples demonstrate the effectiveness of the proposed method.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEngineering applications of artificial intelligence, Jan. 2016, v. 47, p. 81-87en_US
dcterms.isPartOfEngineering applications of artificial intelligenceen_US
dcterms.issued2016-01-
dc.identifier.isiWOS:000367494200009-
dc.identifier.scopus2-s2.0-84930740339-
dc.identifier.eissn1873-6769en_US
dc.identifier.rosgroupid2015003000-
dc.description.ros2015-2016 > Academic research: refereed > Publication in refereed journalen_US
dc.description.validate202208 bcvcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberAMA-0606-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextPolyUen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6597053-
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