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(as of Sep 29, 2024 02:57:02 UTC – Details)
This book presents a self-contained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks. These powerful analytical techniques, which are well established in other fields of physics, are the basis of current developments and offer solutions to pressing open problems in theoretical neuroscience and also machine learning. They enable a systematic and quantitative understanding of the dynamics in recurrent and stochastic neuronal networks.
This book is intended for physicists, mathematicians, and computer scientists and it is designed for self-study by researchers who want to enter the field or as the main text for a one semester course at advanced undergraduate or graduate level. The theoretical concepts presented in this book are systematically developed from the very beginning, which only requires basic knowledge of analysis and linear algebra.
Publisher : Springer; 1st ed. 2020 edition (August 21, 2020)
Language : English
Paperback : 224 pages
ISBN-10 : 3030464431
ISBN-13 : 978-3030464431
Item Weight : 2.31 pounds
Dimensions : 6.1 x 0.51 x 9.25 inches
