This algorithm is fast, incremental learning, and it takes less support vectors!
本算法具有速度快、增量学习、使用的支持向量少等显著优点。
This algorithm is a combination of kernel trick with the covering algorithm, and is used to extract the support vectors in feature space.
该算法将核技巧与覆盖算法相结合，并在特征空间中抽取支持向量。
The algorithm introduced the forgetting factor to get the support vectors at the first training. The number of support vectors is decreased by 28%.
该算法在第一次小样本训练时引入了遗忘因子，该因子使支持向量数减少了28％。
Thus the computational complexity is no longer depend on space dimension, but the number of samples, especially the number of support vectors in each sample.
计算的复杂度不再取决于空间维数，而是取决于样本数，尤其是样本中的支持向量数。
The fuzzy membership based on the affinity among samples for support vector machine effectively distinguishes between support vectors and outliers or noises.
将其应用于模糊支持向量机方法中，较好地将支持向量与含噪声或野值样本区分开。
To solve the problems of the complexity of SVM-MUD model and the number of support vectors, a new algorithm for nonlinear multiuser detection is proposed in the paper.
为了解决支持向量机算法在多用户检测中存在的模型复杂及产生的支持向量数目较多的问题，该文提出一种新的非线性多用户检测算法。
A method for pre-extracting support vectors based on concentric hyperspheres division is presented in this paper, and HD-SVM algorithm based on this method is presented also.
提出了一个基于同心超球面分割的支持向量预抽取方法，并在此基础上给出了HD - SVM训练算法。
A method for pre-extracting support vectors based on concentric hyperspheres division is presented in this paper, and HD-SVM algorithm based on this method is presented also.
提出了一个基于同心超球面分割的支持向量预抽取方法，并在此基础上给出了HD - SVM训练算法。
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