Introduction to Neural Networks

Informationen zum Autor Gurney, Kevin Klappentext Although mathematical ideas underpin the study of neural networks, this book presents the fundamentals without the full mathematical apparatus. The author tackles virtually all aspects of the field, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods; associative memory and Hopfield nets; and self-organization and feature maps. The book provides a concrete focus through several real-world examples. This feature broadens the book's audience to include both students and professionals in cognitive science, psychology, and computer science as well as those involved in the design, construction, and management of networks. Zusammenfassung Although mathematical ideas underpin the study of neural networks, this book presents the fundamentals without the full mathematical apparatus. It tackles various aspects of the field, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; and gradient descent methods. Inhaltsverzeichnis Neural Net - A Preliminary Discussion. The von Neumann Machine and The Symbolic Paradigm. Real Neurons - A Review. Artificial neurons. Non- binary signal communication. Introducing Time. Network Features. Alternative Node Types. Cubic Nodes and Reward. Penalty Training. Drawing Things Together - Some Perspectives.

Product details

• Authors: Kevin Gurney, Kevin (University of Sheffield Gurney, Kevin (University of Sheffield University Gurney, Kevin (University of Sheffield) Gurney, Gurney Kevin, Ucl Press
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 05.08.1997
• EAN: 9781857285031
• ISBN: 978-1-85728-503-1
• No. of pages: 246
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing; COMPUTERS / Data Science / Neural Networks, Neural networks and fuzzy systems, Neural networks & fuzzy systems