The problem of computing the minimum distance between two convex hulls has applications to many areas including robotics, computer graphics and path planning. Moreover, determining the minimum distance between two convex hulls plays a significant role in support vector machines (SVM). In this study, a new algorithm for finding the minimum distance between two convex hulls is proposed and investigated. A convergence of the algorithm is proved and applicability of the algorithm to support vector machines is demostrated. The performance of the new algorithm is compared with the performance of one of the most popular algorithms, the sequential minimal optimization (SMO) method. The new algorithm is simple to understand, easy to implement, and can be more efficient than the SMO method for many SVM problems.
Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc9845 |
Date | 05 1900 |
Creators | Kaown, Dougsoo |
Contributors | Liu, Jianguo, Neuberger, John, Yuan, Xiaohui |
Publisher | University of North Texas |
Source Sets | University of North Texas |
Language | English |
Detected Language | English |
Type | Thesis or Dissertation |
Format | Text |
Rights | Public, Copyright, Kaown, Dougsoo, Copyright is held by the author, unless otherwise noted. All rights reserved. |
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