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020 |
_a9783319099033 _9978-3-319-09903-3 |
||
024 | 7 |
_a10.1007/978-3-319-09903-3 _2doi |
|
035 | _ato000557744 | ||
040 |
_aSpringer _cSpringer _dRU-ToGU |
||
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_aUYQ _2bicssc |
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_aCOM004000 _2bisacsh |
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245 | 1 | 0 |
_aArtificial Neural Networks _helectronic resource _bMethods and Applications in Bio-/Neuroinformatics / _cedited by Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov. |
260 |
_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 |
||
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. _9224332 |
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650 | 0 |
_aNeurosciences. _9302217 |
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650 | 0 |
_aBioinformatics. _9303853 |
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650 | 0 |
_aComputational Intelligence. _9307538 |
|
650 | 0 |
_aControl Engineering. _9304706 |
|
650 | 1 | 4 |
_aEngineering. _9224332 |
650 | 2 | 4 |
_aComputational Intelligence. _9307538 |
650 | 2 | 4 |
_aComputational Biology/Bioinformatics. _9306755 |
650 | 2 | 4 |
_acontrol. _9348605 |
650 | 2 | 4 |
_aNeurosciences. _9302217 |
700 | 1 |
_aKoprinkova-Hristova, Petia. _eeditor. _9414901 |
|
700 | 1 |
_aMladenov, Valeri. _eeditor. _9414900 |
|
700 | 1 |
_aKasabov, Nikola K. _eeditor. _9463333 |
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710 | 2 |
_aSpringerLink (Online service) _9143950 |
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773 | 0 | _tSpringer eBooks | |
830 | 0 |
_aSpringer Series in Bio-/Neuroinformatics, _9451418 |
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856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-09903-3 |
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999 | _c412626 |