TY - CHAP
T1 - An Improved Independent Component Analysis Algorithm and Its Application in Preprocessing of Bearing Sounds
AU - Wen, Guangrui
AU - Qu, Liangsheng
AU - Zhang, Xining
N1 - Publisher Copyright:
© 2006, Springer-Verlag Berlin Heidelberg.
PY - 2006
Y1 - 2006
N2 - Independent Component Analysis (ICA) is known as an efficient technique to separate individual signals from various sources without knowing their prior characteristics. Firstly, the basic principle of ICA is reviewed in Sec 2, and then an improved ICA algorithm based on coordinate rotation (CR-ICA) is proposed. Secondly, two advantages of the CR-ICA algorithm are discussed; the one is that the separation can be carried out without iteration, and the other is that less computation is needed to achieve the same effect. Finally, the experiment in recognition of mixed sound and practical application in preprocessing of bearing sounds proved that the CR-ICA algorithm is better than traditional ICA algorithm in separation precision and computation speed. Moreover, the advantages of the method and the potential for further applications are discussed in the conclusion.
AB - Independent Component Analysis (ICA) is known as an efficient technique to separate individual signals from various sources without knowing their prior characteristics. Firstly, the basic principle of ICA is reviewed in Sec 2, and then an improved ICA algorithm based on coordinate rotation (CR-ICA) is proposed. Secondly, two advantages of the CR-ICA algorithm are discussed; the one is that the separation can be carried out without iteration, and the other is that less computation is needed to achieve the same effect. Finally, the experiment in recognition of mixed sound and practical application in preprocessing of bearing sounds proved that the CR-ICA algorithm is better than traditional ICA algorithm in separation precision and computation speed. Moreover, the advantages of the method and the potential for further applications are discussed in the conclusion.
KW - Blind Source Separation
KW - Independent Component Analysis
KW - Independent Component Analysis
KW - Independent Component Analysis Algorithm
KW - Mixed Signal
UR - https://www.scopus.com/pages/publications/85162938488
U2 - 10.1007/978-3-540-37256-1_7
DO - 10.1007/978-3-540-37256-1_7
M3 - 章节
AN - SCOPUS:85162938488
T3 - Lecture Notes in Control and Information Sciences
SP - 48
EP - 53
BT - Lecture Notes in Control and Information Sciences
PB - Springer Science and Business Media Deutschland GmbH
ER -