KEYWORDS: Signal to noise ratio, Detection and tracking algorithms, Optical spheres, Radar, Pattern recognition, Computer simulations, Control systems, Nickel, Data acquisition, Electronics engineering
Support Vector Data Description (SVDD) is a one-class classification method developed in recent years. It has been used
in many fields because of its good performance and high executive efficiency when there are only one-class training
samples. It has been proven that SVDD has less support vector numbers, less optimization time and faster testing speed
than those of two-class classifier such as SVM. At present, researches and acquirable literatures about SVDD multi-class
classification are little, which restricts the SVDD application. One SVDD multi-class classification algorithm is proposed
in the paper. Based on minimum distance classification rule, the misclassification in multi-class classification is well
solved and by applying the threshold strategy the rejection in multi-class classification is greatly alleviated. Finally, by
classifying range profiles of three targets, the effect of kernel function parameter and SNR on the proposed algorithm is
investigated and the effectiveness of the algorithm is testified by quantities of experiments.
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