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Application of fast incremental LLE to bearing fault feature dimension reduction

  • Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

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.

源语言英语
主期刊名Proceedings - 2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (NISS, ICMIA and NASNIT), ISSDM 2012
423-426
页数4
出版状态已出版 - 2012
活动2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (NISS, ICMIA and NASNIT), ISSDM 2012 - Taipei, 中国台湾
期限: 23 10月 201225 10月 2012

出版系列

姓名Proceedings - 2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (NISS, ICMIA and NASNIT), ISSDM 2012

会议

会议2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (NISS, ICMIA and NASNIT), ISSDM 2012
国家/地区中国台湾
Taipei
时期23/10/1225/10/12

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