000			03970nam a22004095i 4500
650		7	_aRedes neuronales artificiales _2embne _9678664
999			_c103885 _d103885 _x1
001			103885
003			DE-He213
005			20230102113150.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			140902s2015 gw | s |||| 0|eng d
020			_a9783319099033
024	7		_a10.1007/978-3-319-09903-3 _2doi
040			_bspa _dES-MaUEC
050		4	_aQA76.87 _b2015 EB
245	1	0	_aArtificial Neural Networks _bMethods and Applications in Bio-/Neuroinformatics _cedited by Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov.
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (IX, 488 páginas 168 ilustraciones, 70 ilustraciones a color.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
490	0		_aSpringer Series in Bio-/Neuroinformatics, _x2193-9349 ; _v4
490	0		_aEngineering (Springer-11647)
505	0		_aNeural Networks Theory and Models -- New Machine Learning Algorithms for Neural Networks -- Pattern Recognition, Classification and other Neural Network Applications.
520	3		_aThe book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.  .
988			_aEBSPRINGER_2018
700	1		_aKoprinkova-Hristova, Petia. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/nb2014015212 _1http://viaf.org/viaf/305271728/
700	1		_aMladenov, Valeri. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n2004006115 _1http://viaf.org/viaf/307496969/
700	1		_aKasabov, Nikola K. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n94003451 _1http://viaf.org/viaf/85499001/
776	0	8	_iEdición impresa: _z9783319099040
776	0	8	_iEdición impresa: _z9783319099026
776	0	8	_iEdición impresa: _z9783319349503
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-09903-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2019 _dz _ejf _zSI