Overview
- Presents the latest research on artificial neural networks
- Gives emphasis to neural networks and machine learning topics in bio-neuroinformatics
- Edited and written by experts in the field
Part of the book series: Springer Series in Bio-/Neuroinformatics (SSBN, volume 4)
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Table of contents (23 papers)
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Front Matter
Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Artificial Neural Networks
Book Subtitle: Methods and Applications in Bio-/Neuroinformatics
Editors: Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov
Series Title: Springer Series in Bio-/Neuroinformatics
DOI: https://doi.org/10.1007/978-3-319-09903-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-09902-6Published: 11 September 2014
Softcover ISBN: 978-3-319-34950-3Published: 27 September 2016
eBook ISBN: 978-3-319-09903-3Published: 02 September 2014
Series ISSN: 2193-9349
Series E-ISSN: 2193-9357
Edition Number: 1
Number of Pages: IX, 488
Number of Illustrations: 70 b/w illustrations, 98 illustrations in colour
Topics: Computational Intelligence, Computational Biology/Bioinformatics, Control and Systems Theory, Neurosciences