Description: The brain is the most complex computational machine known to science, even though its components (neurons) are slow and unreliable compared to a laptop computer. In this richly illustrated book, Shannon's mathematical theory of information is used to explore the metabolic efficiency of neurons, with special reference to visual perception. Evidence from a diverse range of research papers is used to show how information theory defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style, with a comprehensive glossary, tutorial appendices, explainer boxes, and a list of annotated Further Readings, this book is an ideal introduction to cutting-edge research in neural information theory. Dr James Stone is an Honorary Reader in Vision and Computational Neuroscience at the University of Sheffield, England.
Price: 28.23 USD
Location: East Hanover, New Jersey
End Time: 2024-12-18T17:52:14.000Z
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EAN: 9780993367922
UPC: 9780993367922
ISBN: 9780993367922
MPN: N/A
Format: Paperback, 260 pages, Annotated edition Edition
Author: James V. Stone
Book Title: Principles of Neural Information Theory: Computati
Item Height: 1.1 cm
Item Length: 22.9 cm
Item Weight: 0.34 kg
Item Width: 15.2 cm
Language: Eng
Publisher: Tutorial Introductions
