An Introduction to Neural Information Processing
Springer | Neuroscience | January 23, 2016 | ISBN-10: 9401773912 | 330 pages | pdf | 13.6 mb
Authors: Liang, Peiji, Wu, Si, Gu, Fanji
Clearly illustrates neural information processing models at different levels from single cell to the network
Provided with ample illustrations Written by experts in this field
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.
Number of Illustrations and Tables
165 illus., 45 in colour
Topics
Neurosciences
Computational Biology / Bioinformatics
Information Storage and Retrieval
Artificial Intelligence (incl. Robotics)
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