A01=Kevin Gurney
Adaptive Resonance Theory
Artificial Neural Nets
Artificial Neurons
associative memory models
Author_Kevin Gurney
Axon Hillock
Boolean Vector
Category=UYQN
cognitive modelling
computational neuroscience
Credit Assignment Problem
Delta Rule
Digital Nodes
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
F2 Node
Feedforward Nets
Gradient Descent
Hidden Nodes
Hidden Units
Hopfield Net
Kohonen's Self-organizing Feature Maps
Kohonen’s Self-organizing Feature Maps
Leaky Integrators
learning algorithms
Linear Separability
LTM Trace
neural network simulation techniques
Pattern Space
Real Neurons
Recurrent Net
signal processing networks
synaptic plasticity
Threshold Logic Unit
Vice Versa
Von Neumann Machines
Weight Vector
Product details
- ISBN 9781857285031
- Weight: 380g
- Dimensions: 156 x 234mm
- Publication Date: 05 Aug 1997
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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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.
Gurney; K. University of Sheffield, UK,
