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SVM-based classification selection algorithm for the automatic selection of guide star

机译:基于SVM的分类选择算法,用于自动选择导航星

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A new general method of the automatic selection of guide star, which based on a new dynamic Visual Magnitude Threshold (VMT) hyper-plane and the Support Vector Machines (SVM), is introduced. The high dimensional nonlinear VMT plane can be easily obtained by using the SVM, then the guide star sets are generated by the SVM classifier. The experiment results demonstrate that the catalog obtained by the proposed algorithm has a lot of advantages including, fewer total numbers, smaller catalog size and better distribution uniformity.
机译:介绍了一种新的一般选择导向星的导灯,基于新的动态视觉幅度阈值(VMT)超平面和支持向量机(SVM)。通过使用SVM可以容易地获得高维非线性VMT平面,然后通过SVM分类器产生导向星组。实验结果表明,通过所提出的算法获得的目录具有大量优点,包括更少的总数,更小的目录大小和更好的分布均匀性。

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