Real-time Blind Separation and Deconvolution of Real-world signals

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dc.contributor.advisorKrishnaprasad, P.S.en_US
dc.contributor.authorMao, Yuen_US
dc.contributor.departmentISRen_US
dc.contributor.departmentCAARen_US
dc.date.accessioned2007-05-23T10:14:10Z
dc.date.available2007-05-23T10:14:10Z
dc.date.issued2003en_US
dc.description.abstractWe present a reallistic and robust implementation of Blind Source Separation and Blind Deconvolution. The algorithm is developed from the idea of natraul gradient learning, wavlet filtering and denoising, and the characteristic of different sound source. Several hardware pieciecs are integrated, including a mobile robot, NT workstation and DSP chip to achieve the real time separation of real world signal. Besides, a method of judging the separation performance without knowing the mixing matrix ( mixing filter ) is proposed and verified.en_US
dc.format.extent3689436 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/6378
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; MS 2003-5en_US
dc.relation.ispartofseriesCAAR; MS 2003-1en_US
dc.subjectSensor-Actuator Networksen_US
dc.titleReal-time Blind Separation and Deconvolution of Real-world signalsen_US
dc.typeThesisen_US

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