An Introduction to the Mathematics of Neurons: Modeling in the Frequency Domain (Second Edition, Cambridge Studies in Mathematical Biology)

Frank C. Hoppensteadt

ISBN 10: 0521599296 / ISBN 13: 9780521599290

Published by Cambridge University Press, 1997

About this Item

Cambridge University Press, 1997. Texto en inglés. XX + 211 pp. 23 x 15. Tapa blanda de editorial ilustrada. Sin subrayados ni anotaciones. Buen estado de conservación. ISBN: 0521599296.

Seller Inventory # 058740

Bibliographic Details

• Title: An Introduction to the Mathematics of Neurons: Modeling in the Frequency Domain (Second Edition, Cambridge Studies in Mathematical Biology)
• Publisher: Cambridge University Press
• Publication Date: 1997
• Language: English
• ISBN 10: 0521599296
• ISBN 13: 9780521599290
• Binding: Encuadernación de tapa blanda
• Edition: 2? Edición
• Condition: Bien

About this title

Synopsis

This book describes signal processing aspects of neural networks, how we receive and assess information. Beginning with a presentation of the necessary background material in electronic circuits, mathematical modeling and analysis, signal processing, and neurosciences, it proceeds to applications. These applications include small networks of neurons, such as those used in control of warm-up and flight in moths and control of respiration during exercise in humans. Next, Hoppensteadt develops a theory of mnemonic surfaces and presents material on pattern formation and cellular automata. Finally, the text addresses the large networks, such as the thalamus-reticular complex circuit, that may be involved in focusing attention, and the development of connections in the visual cortex. This book will serve as an excellent text for advanced undergraduates and graduates in the physical sciences, mathematics, engineering, medicine and life sciences.

Book Description

This book describes signal processing aspects of neural networks. It begins with a presentation of the necessary background material in electronic circuits, mathematical modeling and analysis, signal processing, and neurosciences, and then moves on to applications. These applications include small networks of neurons, a theory of mnemonic surfaces, pattern formation and cellular automata, and large networks, such as the complex circuit believed to be involved in focusing attention. This is an excellent text for advanced undergraduates and graduates in the physical sciences, mathematics, engineering, medicine and life sciences.