基于低秩和稀疏表示的轴承故障诊断鲁棒传递子空间学习matlab代码.zip

Low-Rank and Sparse Representation Gaussian (LRSR-G) and Relaxed (LRSR-R) ======== The code in this toolbox implements the "Robust Transfer Subspace Learning Based on Low-Rank and Sparse Representation for Bearing Fault Diagnosis". Quick Testing -- "Single to Image" is used to convert one-dimensional signals to images and extract features of images. Then run the codes in "LRSR-G" and "LRSR-R" to train models using the data from "Single to Image". Citation -- Please dive credit to this paper if this code is useful and helpful for your research.