Analog Circuit Fault Classification Detection Based on Adam-CNN Models-Reference-Cited by-同舟云学术

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Analog Circuit Fault Classification Detection Based on Adam-CNN Models

Published:2024-02-23 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 International Conference on Integrated Circuits and Communication Systems (ICICACS)
language:
Short-container-title:

Author:

Li Jiehao¹,Wu Wenlong²,Zhang Jinghua³,Gao Jianxia¹

Affiliation:

1. North China University of Science and Technology,College of Electrical Engineering,Tangshan,China

2. North China University of Science and Technology,College of Artificial Intelligence,Tangshan,China

3. North China University of Science and Technology,Innovation Education Base,Tangshan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10498131/10498150/10498531.pdf?arnumber=10498531

Reference13 articles.

1. Simultaneous fault localization and detection of analog circuits using deep learning approach

2. Modeling and Optimal Control of Power System Frequency Load Controller by Applying Disturbance in the System by a Modified Version of Firefly Algorithm

3. An efficient method for faults diagnosis in analog circuits based on machine learning classifiers

4. Identification of Triple Negative Breast Cancer Genes Using Rough Set Based Feature Selection Algorithm & Ensemble Classifier;Patil;HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES,2022

5. Statistical property feature extraction based on FRFT for fault diagnosis of analog circuits

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