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Artificial Neural Networks: Methods and Applications in Bio-/Neuroinformatic

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The 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.

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Detail Information

Series Title

Springer Series in Bio-/Neuroinformatics

Call Number

006.3 ART a

Publisher

Cham, Switzerland : Springer Cham., 2015

Collation

IX, 488

Language

English

ISBN/ISSN

978-3-319-09903-3

Classification

006.3

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

Ed. 1

Subject(s)

Computational Intelligence
Neurosciences

Specific Detail Info

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Statement of Responsibility

Editor: Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov

Other Information

Cataloger

umi

Source

https://link.springer.com/book/10.1007/978-3-319-09903-3

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