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An introduction to neural informatio...
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Gu, Fanji.
An introduction to neural information processing
Record Type:
Electronic resources : Monograph/item
Title/Author:
An introduction to neural information processingby Peiji Liang, Si Wu, Fanji Gu.
Author:
Liang, Peiji.
other author:
Wu, Si.
Published:
Dordrecht :Springer Netherlands :2016.
Description:
xi, 328 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Neural networks (Neurobiology)
Online resource:
http://dx.doi.org/10.1007/978-94-017-7393-5
ISBN:
9789401773935$q(electronic bk.)
An introduction to neural information processing
Liang, Peiji.
An introduction to neural information processing
[electronic resource] /by Peiji Liang, Si Wu, Fanji Gu. - Dordrecht :Springer Netherlands :2016. - xi, 328 p. :ill., digital ;24 cm.
Introduction -- Neurobiological basis underlying neural information processing -- Single neuron models -- Neural Coding -- Neural information processing in different brain areas -- Network models of neural information processing.
This book provides an overview of neural information processing research, which is one of the most important branches of neuroscience today. Neural information processing is an interdisciplinary subject, and the merging interaction between neuroscience and mathematics, physics, as well as information science plays a key role in the development of this field. This book begins with the anatomy of the central nervous system, followed by an introduction to various information processing models at different levels. The authors all have extensive experience in mathematics, physics and biomedical engineering, and have worked in this multidisciplinary area for a number of years. They present classical examples of how the pioneers in this field used theoretical analysis, mathematical modeling and computer simulation to solve neurobiological problems, and share their experiences and lessons learned. The book is intended for researchers and students with a mathematics, physics or informatics background who are interested in brain research and keen to understand the necessary neurobiology and how they can use their specialties to address neurobiological problems. It is also provides inspiration for neuroscience students who are interested in learning how to use mathematics, physics or informatics approaches to solve problems in their field.
ISBN: 9789401773935$q(electronic bk.)
Standard No.: 10.1007/978-94-017-7393-5doiSubjects--Topical Terms:
182100
Neural networks (Neurobiology)
LC Class. No.: QP363.3
Dewey Class. No.: 573.85
An introduction to neural information processing
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Introduction -- Neurobiological basis underlying neural information processing -- Single neuron models -- Neural Coding -- Neural information processing in different brain areas -- Network models of neural information processing.
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This book provides an overview of neural information processing research, which is one of the most important branches of neuroscience today. Neural information processing is an interdisciplinary subject, and the merging interaction between neuroscience and mathematics, physics, as well as information science plays a key role in the development of this field. This book begins with the anatomy of the central nervous system, followed by an introduction to various information processing models at different levels. The authors all have extensive experience in mathematics, physics and biomedical engineering, and have worked in this multidisciplinary area for a number of years. They present classical examples of how the pioneers in this field used theoretical analysis, mathematical modeling and computer simulation to solve neurobiological problems, and share their experiences and lessons learned. The book is intended for researchers and students with a mathematics, physics or informatics background who are interested in brain research and keen to understand the necessary neurobiology and how they can use their specialties to address neurobiological problems. It is also provides inspiration for neuroscience students who are interested in learning how to use mathematics, physics or informatics approaches to solve problems in their field.
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EB QP363.3 L693 2016
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http://dx.doi.org/10.1007/978-94-017-7393-5
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