Modified Kernel Marginal Fisher Analysis for Feature Extraction and Its Application to Bearing Fault Diagnosis
The high-dimensional features of defective bearings usually include redundant and irrelevant information, which will degrade the diagnosis performance. Thus, it is critical to extract the sensitive low-dimensional characteristics for improving diagnosis performance. This paper proposes modified kern...
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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Wiley
2016-01-01
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Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2016/1205868 |
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