@inproceedings{bca23088702d4edaac018b08e9dc6936,
title = "Application of fast incremental LLE to bearing fault feature dimension reduction",
abstract = "Focus on incremental local linear embedding (LLE) operation efficiency problem, this paper proposes a fast incremental LLE algorithm. Firstly, we describe briefly the basic principle of LLE algorithm. Secondly, based on the incremental learning principle, the new samples are added, the global coordinates of affect samples are recomputed. Thirdly, the low dimensional embedding coordinates of the incremental samples are formulated by the updated global coordinate matrix and low dimensional embedding coordinates of the given samples, then, using Rayleigh-Ritz accelerated iterative algorithm calculate the global coordinate update. Experiment results show that the proposed algorithm can fastly establish the low dimensional feature for new samples.",
keywords = "dimension reduction, Incremental LLE, Rayleigh-Ritz",
author = "Chengliang Li and Zhongsheng Wang and Hongkai Jiang",
year = "2012",
language = "英语",
isbn = "9788994364193",
series = "Proceedings - 2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (NISS, ICMIA and NASNIT), ISSDM 2012",
pages = "423--426",
booktitle = "Proceedings - 2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (NISS, ICMIA and NASNIT), ISSDM 2012",
note = "2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (NISS, ICMIA and NASNIT), ISSDM 2012 ; Conference date: 23-10-2012 Through 25-10-2012",
}