Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
IEEE Transactions on Computers
An Algorithm for Detecting Unimodal Fuzzy Sets and Its Application as a Clustering Technique
IEEE Transactions on Computers
An Approach to Unsupervised Learning Classification
IEEE Transactions on Computers
Clustering Using a Similarity Measure Based on Shared Near Neighbors
IEEE Transactions on Computers
A Nonparametric Valley-Seeking Technique for Cluster Analysis
IEEE Transactions on Computers
A clustering approach based on Marr's operator with its application to lithologic recognition
Pattern Recognition Letters
Recent Developments in Pattern Recognition
IEEE Transactions on Computers
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The present paper discusses a nonsupervised multicategory problem in terms of nonparametric learning. An algorithm for seeking modes of an unknown multidimensional probability density function (pdf) is considered by employing a hypercubic window function. The convergence proof of the algorithm is also presented. The discriminant function for multicategory problems is constructed by using the estimates of the modes of the multimodal pdf. An application of the mode estimation algorithm to nonparametric signal detection is described. The analytical result shows that our machine nearly converges to the optimal machine without supervision.