Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/34347
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dc.coverage.spatialA neural network approach to blind source separationen_US
dc.date.accessioned2015-02-10T10:41:30Z-
dc.date.available2015-02-10T10:41:30Z-
dc.date.issued2015-02-10-
dc.identifier.urihttp://hdl.handle.net/10603/34347-
dc.description.abstractThis work has focused on development of an Adaptive Self newlineNormalized Radial Basis Function ASNRBF neural network and anUnsupervised Stochastic Gradient Descent learning Algorithm USGDA for newlineBlind Source Separation BSS problem BSS is one of the fundamental and newlinechallenging problems in Artificial Neural Networks ANN and SignalProcessing fields It is an emerging field of fundamental research with many newlinepotential applications and it has garnered much recent research andcommercial interest in the fields such as digital and wireless communications newlinesignal processing acoustics medicine etc The objective of blind sourceseparation is to separate unknown signals that have been mixed together the newlinedesired signals and the mixing matrix are not known and the only availabledata being the mixture signal Hyvarinen et al 2001 newline newlineen_US
dc.format.extentxv, 139p.en_US
dc.languageEnglishen_US
dc.relationp.133-137en_US
dc.rightsuniversityen_US
dc.titleA neural network approach to blind source separationen_US
dc.title.alternativeen_US
dc.creator.researcherMalathi Den_US
dc.subject.keywordblind source separationen_US
dc.subject.keywordinformation and communication engineeringen_US
dc.subject.keywordneural networken_US
dc.description.noteReference p.133-137en_US
dc.contributor.guideGunasekaran Nen_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Information and Communication Engineeringen_US
dc.date.registeredn.d.en_US
dc.date.completed01/02/2010en_US
dc.date.awarded28/02/2010en_US
dc.format.dimensions23cmen_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File30.18 kBAdobe PDFView/Open
02_certificate.pdf20.57 kBAdobe PDFView/Open
03_abstract.pdf25.66 kBAdobe PDFView/Open
04_acknowledgement.pdf20.3 kBAdobe PDFView/Open
05_contents.pdf47.43 kBAdobe PDFView/Open
06_chapter 1.pdf200 kBAdobe PDFView/Open
07_chapter 2.pdf188.72 kBAdobe PDFView/Open
08_chapter 3.pdf869.73 kBAdobe PDFView/Open
09_chapter 4.pdf237.35 kBAdobe PDFView/Open
10_chapter 5.pdf82.35 kBAdobe PDFView/Open
11_appendix.pdf88.61 kBAdobe PDFView/Open
12_references.pdf30.48 kBAdobe PDFView/Open
13_publications.pdf21.08 kBAdobe PDFView/Open
14_vitae.pdf17.33 kBAdobe PDFView/Open


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