LEADER 04435nam 22007455 450 001 9910299665003321 005 20251230065417.0 010 $a3-319-09903-5 024 7 $a10.1007/978-3-319-09903-3 035 $a(CKB)3710000000228710 035 $a(EBL)1967011 035 $a(OCoLC)890701463 035 $a(SSID)ssj0001353939 035 $a(PQKBManifestationID)11764801 035 $a(PQKBTitleCode)TC0001353939 035 $a(PQKBWorkID)11316843 035 $a(PQKB)10548506 035 $a(DE-He213)978-3-319-09903-3 035 $a(MiAaPQ)EBC1967011 035 $a(PPN)181350378 035 $a(EXLCZ)993710000000228710 100 $a20140902d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aArtificial Neural Networks $eMethods and Applications in Bio-/Neuroinformatics /$fedited by Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (487 p.) 225 1 $aSpringer Series in Bio-/Neuroinformatics,$x2193-9357 ;$v4 300 $aDescription based upon print version of record. 311 08$a3-319-09902-7 320 $aIncludes bibliographical references and index. 327 $aNeural Networks Theory and Models -- New Machine Learning Algorithms for Neural Networks -- Pattern Recognition, Classification and other Neural Network Applications. 330 $aThe book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.  . 410 0$aSpringer Series in Bio-/Neuroinformatics,$x2193-9357 ;$v4 606 $aComputational intelligence 606 $aBioinformatics 606 $aControl engineering 606 $aNeurosciences 606 $aComputational Intelligence 606 $aComputational and Systems Biology 606 $aControl and Systems Theory 606 $aNeuroscience 615 0$aComputational intelligence. 615 0$aBioinformatics. 615 0$aControl engineering. 615 0$aNeurosciences. 615 14$aComputational Intelligence. 615 24$aComputational and Systems Biology. 615 24$aControl and Systems Theory. 615 24$aNeuroscience. 676 $a006.3 676 $a570285 676 $a612.8 676 $a620 702 $aKoprinkova-Hristova$b Petia$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMladenov$b Valeri$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKasabov$b Nikola K.$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910299665003321 996 $aArtificial neural networks$91014967 997 $aUNINA