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020 _a9783540744948
_9978-3-540-74494-8
024 7 _a10.1007/978-3-540-74494-8
_2doi
050 4 _aQA76.9.A43
072 7 _aUMB
_2bicssc
072 7 _aCOM051300
_2bisacsh
072 7 _aUMB
_2thema
082 0 4 _a518.1
_223
245 1 0 _aIndependent Component Analysis and Signal Separation
_h[electronic resource] :
_b7th International Conference, ICA 2007, London, UK, September 9-12, 2007, Proceedings /
_cedited by Mike E. Davies, Christopher C. James, Samer A. Abdallah, Mark D. Plumbley.
250 _a1st ed. 2007.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2007.
300 _aXIX, 847 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v4666
505 0 _aTheory -- Algorithms -- Sparse Methods -- Speech and Audio Applications -- Biomedical Applications -- Miscellaneous -- Keynote Talk.
520 _aThis volume contains the papers presented at the 7th International Conference on Independent Component Analysis (ICA) and Source Separation held in L- don, 9–12 September 2007, at Queen Mary, University of London. Independent Component Analysis and Signal Separation is one of the most exciting current areas of research in statistical signal processing and unsup- vised machine learning. The area has received attention from several research communities including machine learning, neural networks, statistical signal p- cessing and Bayesian modeling. Independent Component Analysis and Signal Separation has applications at the intersection of many science and engineering disciplinesconcernedwithunderstandingandextractingusefulinformationfrom data as diverse as neuronal activity and brain images, bioinformatics, com- nications, the World Wide Web, audio, video, sensor signals, or time series. This year’s event was organized by the EPSRC-funded UK ICA Research Network (www.icarn.org). There was also a minor change to the conference title this year with the exclusion of the word‘blind’. The motivation for this was the increasing number of interesting submissions using non-blind or semi-blind techniques that did not really warrant this label. Evidence of the continued interest in the ?eld was demonstrated by the healthy number of submissions received, and of the 149 papers submitted just over two thirds were accepted.
650 0 _aAlgorithms.
650 0 _aComputer science.
650 0 _aCoding theory.
650 0 _aInformation theory.
650 0 _aMathematical statistics
_xData processing.
650 0 _aData mining.
650 0 _aSignal processing.
650 1 4 _aAlgorithms.
650 2 4 _aTheory of Computation.
650 2 4 _aCoding and Information Theory.
650 2 4 _aStatistics and Computing.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aSignal, Speech and Image Processing.
700 1 _aDavies, Mike E.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aJames, Christopher C.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aAbdallah, Samer A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aPlumbley, Mark D.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540744931
776 0 8 _iPrinted edition:
_z9783540842958
830 0 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v4666
856 4 0 _uhttps://doi.org/10.1007/978-3-540-74494-8
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912 _aZDB-2-SXCS
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