Gerasimos G. Rigatos

eBook, PDF

Advanced Models of Neural Networks (eBook, PDF)

Nonlinear Dynamics and Stochasticity in Biological Neurons

Beschreibung

Suitable for researchers engaged with neural networks and dynamical systems theory

Introduces advanced models of neural networks

Includes several chapters suitable for related postgraduate courses in engineering, computer science, mathematics, physics and biology

Technische Details

• Geräte: PC
• ohne Kopierschutz
• Größe: 9.12MB

Barrierefreiheit

• Text-to-Speech

Autor

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.

Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 275
• Erscheinungstermin: 27. August 2014
• Englisch
• ISBN-13: 9783662437643
• Artikelnr.: 43792016

Rezensionen

"Several chapters deal with standard questions like control, synchronization, and estimation. Rigatos uses a clever linearization technique, and then applies variants of linear control techniques to solve these problems for nonlinear models. ... I recommend this book to those interested in neural nets who won't be put off by the density of the mathematics." (Paul Cull, Computing Reviews, December, 2014)