A Novel Feature Extraction Method for Soft Faults in Nonlinear Analog Circuits Based on LMD-GFD and KPCA
To obtain feature information of soft faults in non-linear analog circuits in a more effective way, this paper proposed a novel feature extraction method for soft faults in non-linear analog circuits based on Local Mean Decomposition-Generalized Fractal Dimension (LMD-GFD) and Kernel Principal Compo...
Guardado en:
Autores principales: | Xinmiao Lu*, Jiaxu Wang, Qiong Wu, Yuhan Wei, Yanwen Su |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/c6061fe296b94018ac1ff1306c4a71ea |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
An Enhanced Ensemble Learning-Based Fault Detection and Diagnosis for Grid-Connected PV Systems
por: Khaled Dhibi, et al.
Publicado: (2021) -
KPCA over PCA to assess urban resilience to floods
por: Satour Narjiss, et al.
Publicado: (2021) -
Slice-Based Analog Design
por: Pablo Walker, et al.
Publicado: (2021) -
A robust study on the listeriosis disease by adopting fractal-fractional operators
por: Ebenezer Bonyah, et al.
Publicado: (2022) -
Analog and Mixed Signal Circuit Design Techniques in Flexible Unipolar a-IGZO TFT Technology: Challenges and Recent Trends
por: Mohammad Zulqarnain, et al.
Publicado: (2021)