Neural networks have recently received a great deal of attention in many fields of study. The excitement stems from the fact that these networks are attempts to model the capabilities of the human brain. People are naturally attracted by attempts to create human-like machines, a Frankenstein obsession, if you will. On a practical level the human brain has many features that are desirable in an electronic computer. The human brain has the ability to generalize from abstract ideas, recognize patterns in the presence of noise, quickly recall memories, and withstand localized damage. From a statistical perspective neural networks are interesting because of their potential use in prediction and classification problems.
Neural networks have been used for a wide variety of applications where statistical methods are traditionally employed. They have been used in classification problems such as identifying underwater sonar contacts, and predicting heart problems in patients. They have also been used in such diverse areas as diagnosing hypertension, and recognizing speech. In time series applications they have been used in predicting stock market performance. Neural networks are currently the preferred tool in predicting protein secondary structures. As statisticians or users of statistics, we would normally solve these problems through classical statistical models such as discriminant analysis, logistic regression, Bayes and other types of classifiers, multiple regression, and time series models such as ARIMA and other forecasting methods. It is therefore time to recognize neural networks as a potential tool for data analysis.
Several authors have done comparison studies between statistical methods and neural networks. These works tend to focus on performance comparisons and use specific problems as examples. There are a number of good introductory articles on neural networks, usually located in various trade journals. For instance, Lippmann (1987) provides an excellent overview of neural networks for the signal processing community.......
