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Neural Networks
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Neural Networks



96 pages | SAGE Publications, Inc
Neural networks, adaptive statistical models based on an analogy with the structure of the brain, can be used to estimate the parameters of some population using one (or a few) exemplars at a time. This book introduces readers to the basic models of neural networks and compares and contrasts these models using other statistical models. Through the use of examples that can be computed by hand or with a simple calculator, the authors describe and explain the various models.
 
Introduction
 
The Perceptron
 
Linear Autoassociative Memories
 
Linear Heteroassociative Memories
 
Error Backpropagation
 
Useful References

Herve Abdi

Hervé Abdi was born in France where he grew up. He received an M.S. in Psychology from the University of Franche-Comté (France) in 1975, an M.S. (D.E.A.) in Economics from the University of Clermond-Ferrand (France) in 1976, an M.S. (D.E.A.) in Neurology from the University Louis Pasteur in Strasbourg (France) in 1977, and a Ph.D. in Mathematical Psychology from the University of Aix-en-Provence (France) in 1980. He was an assistant professor in the University of Franche-Comté (France) in 1979, an associate professor in the University of Bourgogne at Dijon (France) in 1983, a full professor in the University of Bourgogne at Dijon (France)... More About Author

Dominique Valentin

Betty Edelman

SAGE Research Methods is a research methods tool created to help researchers, faculty and students with their research projects. SAGE Research Methods links over 175,000 pages of SAGE’s renowned book, journal and reference content with truly advanced search and discovery tools. Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. Since SAGE Research Methods focuses on methodology rather than disciplines, it can be used across the social sciences, health sciences, and more.