Source Separation Based On Nonnegative Matrix Factorization and Independent Component Correlation Algorithm

被引：0
|
作者：
Kong, Xiangwei [1 ]
Liang, Lin [1 ,2 ]
Yang, Tianshe [3 ]
Zhao, Jing [3 ]
Wang, Xuhua [3 ]
机构：
[1] Xi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Peoples R China
[2] Xi An Jiao Tong Univ, Educ Minist Modern Design & Rotor Bearing Syst, Key Lab, Xian 710049, Peoples R China
[3] China Xian Satellite Control Ctr, Xian, Peoples R China
来源：
2015 8TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP) | 2015年
关键词：
Vibration Source Analysis; Nonnegative Matrix Factorization; Source Separation;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Because the initialization of Nonnegative Matrix Factorization (NMF) has a great impact to the final result, a new method that combines Independent Component Analysis (ICA) with NMF is put forward. Firstly, ICA is used to process the raw data and the initial value of NMF can be obtatined. Secondly, according to the characters of machine faults, the Hierarchical Alternating Least Squares (HALS-CR) is adopted to extract fault feature from complex system. Finally, simulations and application data show that the proposed approach is effective in improving the separation of traditional NMF.
引用
收藏
页码：1614 / 1619
页数：6
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