Using prototypes to solve problems in neural net classifiers

It is shown that using the notion of `prototype´ in neural net classifiers can solve several problems that a nonlinear classifier might encounter. This has motivated the development of a new neural classifier named NNP. The author presents an empirical evaluation on the advantages of NNP over other classifiers