An effective method using clustering-based adaptive decomposition and editing-based diversified oversamping for multi-class imbalanced datasets

Author(s):  
Xiangtao Chen ◽  
Lan Zhang ◽  
Xiaohui Wei ◽  
Xinguo Lu
Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1231
Author(s):  
Yunbo Shi ◽  
Juanjuan Zhang ◽  
Jingjing Jiao ◽  
Rui Zhao ◽  
Huiliang Cao

High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 123358-123374
Author(s):  
Saptarshi Bej ◽  
Kristian Schulz ◽  
Prashant Srivastava ◽  
Markus Wolfien ◽  
Olaf Wolkenhauer
Keyword(s):  

2014 ◽  
Vol 26 (5) ◽  
pp. 1041-1054 ◽  
Author(s):  
William A. Young ◽  
Scott L. Nykl ◽  
Gary R. Weckman ◽  
David M. Chelberg

2015 ◽  
Vol 73 ◽  
pp. 1-17 ◽  
Author(s):  
Saleh Alshomrani ◽  
Abdullah Bawakid ◽  
Seong-O Shim ◽  
Alberto Fernández ◽  
Francisco Herrera

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