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Proceedings Paper

Multiple-resolution clustering for recursive divide and conquer
Author(s): Steven E. Noel; Harold H. Szu
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Paper Abstract

In recent work, a recursive divide-and-conquer approach was developed for path-minimization problems such as the traveling salesman problem (TSP). The approach is based on multiple-resolution clustering to decompose a problem into minimally-dependent parts. It is particularly effective for large-scale, fractal data sets, which exhibit clustering on all scales, and hence at all resolutions. This leads to the application of wavelets for performing the necessary multiple-resolution clustering. While the general topic of multiple-resolution clustering via wavelets is relatively immature, it has been explored for certain specific applications. However, nothing in the literature addresses the specific type of multiple-resolution clustering needed for the divide-and-conquer approach. That is the primary goal of this paper.

Paper Details

Date Published: 3 April 1997
PDF: 14 pages
Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); doi: 10.1117/12.271725
Show Author Affiliations
Steven E. Noel, Naval Surface Warfare Ctr. (United States)
Harold H. Szu, Naval Surface Warfare Ctr. (United States)

Published in SPIE Proceedings Vol. 3078:
Wavelet Applications IV
Harold H. Szu, Editor(s)

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