Neural Networks / Edition 1 available in Paperback
- Pub. Date:
- SAGE Publications
This book provides the first accessible introduction to neural network analysis as a methodological strategy for social scientists. The author details numerous studies and examples which illustrate the advantages of neural network analysis over other quantitative and modeling methods in widespread use. Methods are presented in an accessible style for readers who do not have a background in computer science. The book provides a history of neural network methods, a substantial review of the literature, detailed applications, coverage of the most common alternative models and examples of two leading software packages for neural network analysis.
About the Author
Table of ContentsIntroductionThe PerceptronLinear Autoassociative MemoriesLinear Heteroassociative MemoriesError BackpropagationUseful References
From One of the Authors
Here is a brief description of the book: Neural networks are adaptive statistical models based on an analogy with the structure of the brain. They can be used to estimate the parameters of some population using only one (or a few) exemplars at a time. Neural Networks introduces readers to the basic models of neural networks and compares and contrasts these models with the use of 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 following: the perceptron, including the Widrow-Hoff learning rule, state space, and how the perceptron is akin to discriminate analysis; the linear associative memory, including Hebbian learning and how autoassociative memory is closely related to principal component analysis; the linear heteroassociative memory as a generalization of the perceptron and how it corresponds to multiple linear regression; and backpropagation networks and their use in the estimation of values of parameters via a gradient descent algorithm in problems equivalent to nonlinear regression. Audience: Researchers in psychology, economics, sociology, and statistics who have been looking for a brief introduction to neural networks will find this book very useful.
Herve Abdi (firstname.lastname@example.org), Co-Author