An introduction to neural networks /
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| Author / Creator: | Anderson, James A. |
|---|---|
| Imprint: | Cambridge, Mass. : MIT Press, c1995. |
| Description: | xi, 650 p. : ill. ; 27 cm. |
| Language: | English |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/1755342 |
Table of Contents:
- Introduction
- Acknowledgements
- Properties of Single Neurons
- Synaptic Integration and Neuron Models
- Essential Vector Operations
- Lateral Inhibition and Sensory Processing
- Simple Matrix Operations
- The Linear Associator: Background and Foundations
- The Kinear Associator: Simulations
- Early Network Models: The Perceptron
- Gradient Descent Algorithms
- Representation of Information
- Applications of Simple Associators: Concept Formation and Object Motion
- Energy and Neural Networks: Hopfield Networks and Boltzmann Machines
- Nearest Neighbor Models
- Adaptive Maps
- The BSB Model: A Simple Nonlinear Autoassociative Neural Network
- Associative Computation
- Teaching Arithmetic to a Neural Network
- Afterword
- Index
