000			03627nam a22006375i 4500
001			978-3-642-15995-4
003			DE-He213
005			20160624102149.0
007			cr nn 008mamaa
008			100919s2010 gw | s |||| 0|eng d
020			_a9783642159954 _9978-3-642-15995-4
024	7		_a10.1007/978-3-642-15995-4 _2doi
050		4	_aQ337.5
050		4	_aTK7882.P3
072		7	_aUYQP _2bicssc
072		7	_aCOM016000 _2bisacsh
082	0	4	_a006.4 _223
245	1	0	_aLatent Variable Analysis and Signal Separation _h[electronic resource] : _b9th International Conference, LVA/ICA 2010, St. Malo, France, September 27-30, 2010. Proceedings / _cedited by Vincent Vigneron, Vicente Zarzoso, Eric Moreau, Rémi Gribonval, Emmanuel Vincent.
260		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
300			_aXVIII, 655 p. 182 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Computer Science, _x0302-9743 ; _v6365
505	0		_aSpeech and Audio Applications -- Convolutive Signal Separation -- The 2010 Signal Separation Evaluation Campaign (SiSEC2010) -- Audio -- Theory -- Telecom -- Tensor Factorizations -- Sparsity I -- Sparsity; Biomedical Applications -- Non-negativity; Image Processing Applications -- Tensors; Joint Diagonalization -- Sparsity II -- Biomedical Applications -- Emerging Topics.
520			_aThis book constitutes the proceedings of the 9th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2010, held in St. Malo, France, in September 2010. The 25 papers presented were carefully reviewed and selected from over hundred submissions. The papers collected in this volume demonstrate that the research activity in the field continues to gather theoreticians and practitioners, with contributions ranging range from abstract concepts to the most concrete and applicable questions and considerations. Speech and audio, as well as biomedical applications, continue to carry the mass of the considered applications. Unsurprisingly the concepts of sparsity and non-negativity, as well as tensor decompositions, have become predominant, reflecting the strong activity on these themes in signal and image processing at large.
650		0	_aComputer science.
650		0	_aSoftware engineering.
650		0	_aComputer software.
650		0	_aComputational complexity.
650		0	_aComputer simulation.
650		0	_aComputer vision.
650		0	_aOptical pattern recognition.
650	1	4	_aComputer Science.
650	2	4	_aPattern Recognition.
650	2	4	_aImage Processing and Computer Vision.
650	2	4	_aSimulation and Modeling.
650	2	4	_aAlgorithm Analysis and Problem Complexity.
650	2	4	_aDiscrete Mathematics in Computer Science.
650	2	4	_aSpecial Purpose and Application-Based Systems.
700	1		_aVigneron, Vincent. _eeditor.
700	1		_aZarzoso, Vicente. _eeditor.
700	1		_aMoreau, Eric. _eeditor.
700	1		_aGribonval, Rémi. _eeditor.
700	1		_aVincent, Emmanuel. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642159947
786			_dSpringer
830		0	_aLecture Notes in Computer Science, _x0302-9743 ; _v6365
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-15995-4
942			_2EBK9327 _cEBK
999			_c38621 _d38621