logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Advanced Models Of Neural Networks Nonlinear Dynamics And Stochasticity In Biological Neurons 1st Edition Gerasimos G Rigatos Auth

  • SKU: BELL-4935044
Advanced Models Of Neural Networks Nonlinear Dynamics And Stochasticity In Biological Neurons 1st Edition Gerasimos G Rigatos Auth
$ 31.00 $ 45.00 (-31%)

4.0

26 reviews

Advanced Models Of Neural Networks Nonlinear Dynamics And Stochasticity In Biological Neurons 1st Edition Gerasimos G Rigatos Auth instant download after payment.

Publisher: Springer-Verlag Berlin Heidelberg
File Extension: PDF
File size: 8.84 MB
Pages: 275
Author: Gerasimos G. Rigatos (auth.)
ISBN: 9783662437636, 9783662437643, 3662437635, 3662437643
Language: English
Year: 2015
Edition: 1

Product desciption

Advanced Models Of Neural Networks Nonlinear Dynamics And Stochasticity In Biological Neurons 1st Edition Gerasimos G Rigatos Auth by Gerasimos G. Rigatos (auth.) 9783662437636, 9783662437643, 3662437635, 3662437643 instant download after payment.

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.

Related Products