000 03812nam a22005415i 4500
001 978-3-319-09903-3
003 DE-He213
005 20200421112046.0
007 cr nn 008mamaa
008 140902s2015 gw | s |||| 0|eng d
020 _a9783319099033
_9978-3-319-09903-3
024 7 _a10.1007/978-3-319-09903-3
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aArtificial Neural Networks
_h[electronic resource] :
_bMethods and Applications in Bio-/Neuroinformatics /
_cedited by Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aIX, 488 p. 168 illus., 70 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Bio-/Neuroinformatics,
_x2193-9349 ;
_v4
505 0 _aNeural Networks Theory and Models -- New Machine Learning Algorithms for Neural Networks -- Pattern Recognition, Classification and other Neural Network Applications.
520 _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.  .
650 0 _aEngineering.
650 0 _aNeurosciences.
650 0 _aBioinformatics.
650 0 _aComputational intelligence.
650 0 _aControl engineering.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aComputational Biology/Bioinformatics.
650 2 4 _aControl.
650 2 4 _aNeurosciences.
700 1 _aKoprinkova-Hristova, Petia.
_eeditor.
700 1 _aMladenov, Valeri.
_eeditor.
700 1 _aKasabov, Nikola K.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319099026
830 0 _aSpringer Series in Bio-/Neuroinformatics,
_x2193-9349 ;
_v4
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-09903-3
912 _aZDB-2-ENG
942 _cEBK
999 _c56917
_d56917