Independent Component Analysis and Blind Signal Separation

Independent Component Analysis and Blind Signal Separation

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tionsalso, apartfromsignalprocessing, withother?eldssuchasstatisticsandarti?cial neuralnetworks. As long as we can ?nd a system that emits signals propagated through a mean, andthosesignalsarereceivedbyasetofsensorsandthereisaninterestinrecovering the originalsources, we have a potential?eld ofapplication forBSS and ICA. Inside thatwiderangeofapplicationswecan?nd, forinstance:noisereductionapplications, biomedicalapplications, audiosystems, telecommunications, andmanyothers. This volume comes out just 20 years after the ?rst contributionsin ICA and BSS 1 appeared . Thereinafter, the numberof research groupsworking in ICA and BSS has been constantly growing, so that nowadays we can estimate that far more than 100 groupsareresearchinginthese?elds. Asproofoftherecognitionamongthescienti?ccommunityofICAandBSSdev- opmentstherehavebeennumerousspecialsessionsandspecialissuesinseveralwell- 1 J.Herault, B.Ans, a€œCircuits neuronaux An synapses modi?ables: dAccodage de messages c- posites para apprentissage non supervisea€, C.R. de l'AcadAcmie des Sciences, vol. 299, no. III-13, pp.525a€“528, 1984.Fifth International Conference, ICA 2004, Granada, Spain, September 22-24, 2004, Proceedings Carlos G. Puntonet, Alberto Prieto ... Up to this point, we have reduced the problem of estimating the mixing matrix A to the problem of estimating the n peaks of an (m aˆ’ 1)-dimensional PDF, since those peaks define the spherical angles that parametrize the n columns of the mixing matrix. It is well known thatanbsp;...

Title:Independent Component Analysis and Blind Signal Separation
Author: Carlos G. Puntonet, Alberto Prieto
Publisher:Springer Science & Business Media - 2004-09-17

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