Authors:
- Explores questions related to the biological underpinning for models of neural networks
- Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities
- Provides all necessary mathematical basics for application to the theory of neural networks
Part of the book series: Nonlinear Systems and Complexity (NSCH, volume 9)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided.
Keywords
- Artificial Intelligence
- Chaotic Neural Networks
- Cohen-Grossberg Neural Networks
- Computational Neural Networks
- Impulsive Differential Equations
- Lyapnov-Razumikhim Method
- Neural Networks
- Piecewise Constant Argument
- Recurrent Neural Networks
- State-dependent Moments of Time
- complexity
- ordinary differential equations
Authors and Affiliations
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Department of Mathematics, Middle East Technical University (METU), Ankara, Turkey
Marat Akhmet
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Department of Mathematics, Adnan Menderes University, Aydin, Turkey
Enes Yılmaz
Bibliographic Information
Book Title: Neural Networks with Discontinuous/Impact Activations
Authors: Marat Akhmet, Enes Yılmaz
Series Title: Nonlinear Systems and Complexity
DOI: https://doi.org/10.1007/978-1-4614-8566-7
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Science+Business Media New York 2014
Hardcover ISBN: 978-1-4614-8565-0Published: 31 October 2013
Softcover ISBN: 978-1-4939-4598-6Published: 23 August 2016
eBook ISBN: 978-1-4614-8566-7Published: 30 October 2013
Series ISSN: 2195-9994
Series E-ISSN: 2196-0003
Edition Number: 1
Number of Pages: XI, 168
Number of Illustrations: 5 b/w illustrations, 23 illustrations in colour
Topics: Complexity, Artificial Intelligence, Biomedical Engineering and Bioengineering, Ordinary Differential Equations, Mathematical Models of Cognitive Processes and Neural Networks