
An Introduction to Neural Networks
- Publisher's listprice GBP 75.00
-
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 3 796 Ft off)
- Discounted price 34 162 Ft (32 535 Ft + 5% VAT)
37 957 Ft
Availability
Out of print
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 5 August 1997
- ISBN 9781857286731
- Binding Hardback
- No. of pages248 pages
- Size 234x156 mm
- Weight 498 g
- Language English 0
Categories
Short description:
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.
MoreLong description:
Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.
MoreTable of Contents:
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.
More
An Introduction to Neural Networks
37 957 HUF