A new bearing fault detection approach based on relevance vector machine (RVM) is presented.
针对轴承故障检测问题，提出一种基于相关向量机(RVM)的故障检测方法。
A new regression algorithm of an adaptive reduced relevance vector machine is proposed to estimate the illumination chromaticity of an image for the purpose of color constancy.
摘要提出了一种新的自适应约简相关向量机回归算法来估计图像的光照色度以达到色彩一致性目的。
The relevance vector machine (RVM) is used to process the hyperspectral image in this paper to estimate the classifiers precisely in the high dimensional space with limited training samples.
将关联向量机应用于高光谱影像分类， 实现高维空间中训练样本不足时分类器的精确建模。
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