K-Nearest Neighbor Attractor-Based Neural Network and the Optimal Linear Discriminatory Filter Classifier

摘要

The K-Nearest Neighbor Attractor-based Neural Network and the Optimal Linear Discriminatory Filter Classifier are feature-based classifiers that are trained via supervised learning using a training set of feature vectors. They were developed by the author and successfully used in several applications where they were 'and-ed.' Results using these classifiers have been published, but comprehensive descriptions of them have not appeared in the literature. This paper presents their detailed descriptions.