About this book
Several theories consider the brain to be a network of neurons that process perception with simple activation functions. Real neurons, however, are far more intricate.Through reviews of literature and results from original experiments, Neural Cell Behavior and Fuzzy Logic offers a comprehensive look at these complex systems, supplying trustworthy evidence that neurons can predict the consequences of input signals and transiently change their own excitability to suit. The book also examines how fuzzy logic, the computing of perceptions, can be used to provide a theoretical description of real neuron behavior, and as a model for the "logic" the brain uses to describe environments and make decisions. This book includes sections for general and advanced readers, and will be particularly useful to neuroscience students, academics and researchers as well as to mathematicians and theoretical physicists.
About the authors:
Uziel Sandler is a professor in the Department of Applied Mathematics at Jerusalem College of Technology in Israel. Dr. Sandler is an expert in nonlinear properties and critical behavior of condensed matter, evolutionary computations, and fuzzy sets theory. He has published two books and more than 70 academic articles in scientific journals, and is a member in several worldwide committees in the aforementioned fields.
Professor Lev E.Tsitolovsky is a senior researcher in the Life Science Department of Bar-Ilan University in Israel. He is a renowned expert in the fields of thorough mechanisms of learning, memory , and motivation , and has published over 100 scientific papers and reviews on these topics. Recently, his discovery of excitable membrane plasticity anticipated modern development in this area.
Editors and affiliations
- Book Title Neural Cell Behavior and Fuzzy Logic
- DOI https://doi.org/10.1007/978-0-387-09543-1
- Copyright Information Springer Science+Business Media, LLC 2008
- Publisher Name Springer, Boston, MA
- eBook Packages Biomedical and Life Sciences Biomedical and Life Sciences (R0)
- Hardcover ISBN 978-0-387-09542-4
- Softcover ISBN 978-1-4419-3492-5
- eBook ISBN 978-0-387-09543-1
- Edition Number 1
- Number of Pages XII, 478
- Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
Computer Appl. in Life Sciences
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