A Novel General Feature Enhancement Method Based on Genetic Programming for Improving RF Circuit Fault Diagnosis Using Machine Learning

Radio frequency (RF) circuits play a crucial role in numerous fields such as communication, radar, and navigation. However, due to their high operating frequencies, they are prone to failures under the influence of environmental factors and parasitic parameters. Existing methods for diagnosing RF ci...

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Veröffentlicht in:	Circuits, systems, and signal processing Jg. 44; H. 12; S. 8877 - 8900
Hauptverfasser:	Wu, Kunping, Long, Bing, Bu, Zhiyuan, Wang, Jingyuan, Liu, Zhen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2025 Springer Nature B.V
Schlagworte:	Accuracy Circuits Circuits and Systems Classification Deep learning Electrical Engineering Electronics and Microelectronics Engineering Failure Fault diagnosis Genetic algorithms Instrumentation Machine learning Methods Neural networks Physical properties Radio frequency Signal,Image and Speech Processing Support vector machines Time-frequency analysis Fault diagnosis Feature enhancement Genetic programming (GP) Machine learning Radio frequency (RF) circuit
ISSN:	0278-081X, 1531-5878
Online-Zugang:	Volltext
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