Cantitate/Preț
Produs

Advanced Models of Neural Networks: Nonlinear Dynamics and Stochasticity in Biological Neurons

Autor Gerasimos G. Rigatos
en Limba Engleză Hardback – 9 sep 2014
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.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 63258 lei  43-57 zile
  Springer Berlin, Heidelberg – 23 aug 2016 63258 lei  43-57 zile
Hardback (1) 63872 lei  43-57 zile
  Springer Berlin, Heidelberg – 9 sep 2014 63872 lei  43-57 zile

Preț: 63872 lei

Preț vechi: 79839 lei
-20% Nou

Puncte Express: 958

Preț estimativ în valută:
12224 12697$ 10154£

Carte tipărită la comandă

Livrare economică 03-17 februarie 25

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783662437636
ISBN-10: 3662437635
Pagini: 275
Ilustrații: XXIII, 275 p. 135 illus., 91 illus. in color.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.59 kg
Ediția:2015
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Modelling Biological Neurons in Terms of Electrical Circuits.- Systems Theory for the Analysis of Biological Neuron Dynamics.- Bifurcations and Limit Cycles in Models of Biological Systems.- Oscillatory Dynamics in Biological Neurons.- Synchronization of Circadian Neurons and Protein Synthesis Control.- Wave Dynamics in the Transmission of Neural Signals.- Stochastic Models of Biological Neuron Dynamics.- Synchronization of Stochastic Neural Oscillators Using Lyapunov Methods.- Synchronization of Chaotic and Stochastic Neurons Using Differential Flatness Theory.- Attractors in Associative Memories with Stochastic Weights.- Spectral Analysis of Neural Models with Stochastic Weights.- Neural Networks Based on the Eigenstates of the Quantum Harmonic Oscillator.- Quantum Control and Manipulation of Systems and Processes at Molecular Scale.- References.- Index.

Notă biografică

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.

Textul de pe ultima copertă

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.

Caracteristici

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