hidden kernel feature space 隐核特征空间
The received mixing signals are first mapped to high-dimensional kernel feature space, and a feature vector basis given by the fitness function of the kernel feature space is constructed.
所接收的混合信号首先被映射到高维的内核特征空间,和由内核特征空间上的适应度函数给出的特征矢量的基础构造。
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。
Mean shift based image segmentation algorithm is a kind of kernel density estimation based feature space analysis algorithm, and the nature of it is statistical optimization.
均值漂移算法是一种基于核密度梯度估计的特征空间分析算法,其实质是一种统计优化过程。
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