Intermittent Fault Recognition of Analog Circuits in the Presence of Outliers via Density Peak Clustering With Adaptive Weighted Distance
Author:
Affiliation:
1. College of Automation, Chongqing University, Chongqing, China
2. College of Control Science and Engineering, Shandong University, Jinan, China
Funder
National Natural Science Foundation of China
Shandong Provincial Natural Science Foundation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10152544/10122861.pdf?arnumber=10122861
Reference35 articles.
1. Adaptive multiscale and dual subnet convolutional auto-encoder for intermittent fault detection of analog circuits in noise environment
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3. Self-supervised intermittent fault detection for analog circuits guided by prior knowledge
4. Intermittent Failure Dynamics Characterization
5. An Online Diagnosis Method for Sensor Intermittent Fault Based on Data-Driven Model
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