Advanced Models of Neural Networks

Gerasimos G. Rigatos

ISBN 10: 3662515571 / ISBN 13: 9783662515570

Published by Springer Berlin Heidelberg Aug 2016, 2016

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory. It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory. 300 pp. Englisch.

Seller Inventory # 9783662515570

Bibliographic Details

• Title: Advanced Models of Neural Networks
• Publisher: Springer Berlin Heidelberg Aug 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 3662515571
• ISBN 13: 9783662515570
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory.

It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.

About the Author

Dr. Gerasimos Rigatos received his Ph.D. from the Dept. of Electrical and Computer Engineering of the National Technical University of Athens, Greece. He had a postdoctoral position at IRISA, Rennes, France, he was an invited professor at the Université Paris XI (Institut d'Eléctronique Fondamentale) and a lecturer in the Dept. of Engineering of Harper-Adams University College, UK. He is now a researcher in the Unit of Industrial Automation, Industrial Systems Institute, Patras, Greece. His research interests include computational intelligence, adaptive systems, mechatronics, robotics and control, optimization and fault diagnosis.