학술논문
Clustering on a hypercube multicomputer
Document Type
Conference
Source
[1990] Proceedings. 10th International Conference on Pattern Recognition Pattern Recognition, 1990. Proceedings., 10th International Conference on. ii:532-536 vol.2 1990
Subject
Language
Abstract
Squared-error clustering algorithms for single-instruction multiple-data (SIMD) hypercubes are presented. These algorithms are asymptotically faster than previous algorithms and require less memory per processing element. For a clustering problem with N patterns, M features per pattern, and K clusters, the algorithms complete it in O(K+log NM) steps on NM processor hypercubes. This is optimal up to a constant factor. Experimental results from a commercially available multiple-instruction multiple-data (MIMD) medium-grain hypercube show that the clustering problem can be solved efficiently by the machines.ETX