Mathematical Foundations of Neuroscience 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Mathematical Foundations of Neuroscience

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G. Bard Ermentrout 作者
Springer
譯者
2010-7-8 出版日期
422 頁數
USD 74.95 價格
叢書系列
9780387877075 圖書編碼

Mathematical Foundations of Neuroscience 在線電子書 圖書標籤: 數學  計算  腦科學  神經科學  生物-生物數學  生物  數學-ComputationalNeuroscience  ml   


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Mathematical Foundations of Neuroscience 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Mathematical Foundations of Neuroscience 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Mathematical Foundations of Neuroscience 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Mathematical Foundations of Neuroscience 在線電子書 著者簡介

Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University.


Mathematical Foundations of Neuroscience 在線電子書 著者簡介


Mathematical Foundations of Neuroscience 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Mathematical Foundations of Neuroscience 在線電子書 圖書描述

This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University.

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