Recognition of Power Quality Disturbances Using Hybrid Algorithm Based on Combined Features of Stockwell Transform and Hilbert Transform-Reference-Cited by-同舟云学术

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Recognition of Power Quality Disturbances Using Hybrid Algorithm Based on Combined Features of Stockwell Transform and Hilbert Transform

Published:2020-02 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS)
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Author:

Pandya Vishakha,Agarwal Sunil,Mahela Om Prakash,Choudhary Sunita

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9082706/9086959/09087113.pdf?arnumber=9087113

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimization of Convolutional Neural Networks for Classifying Power Quality Disturbances Using Wavelet Synchrosqueezed Transform;Traitement du Signal;2024-04-30

2. Integration of BIST Module for Error Bit Detection in SPI Protocol;Lecture Notes in Electrical Engineering;2024

3. Classification of Power Quality Disturbances using the Unique Combination of Hilbert Transform, Image Processing and K-Nearest Neighbor;2022 International Conference on Emerging Trends in Engineering and Medical Sciences (ICETEMS);2022-11-18

4. Hybrid signal processing technique to design smart meter for detection of voltage amplitude disturbances;Active Electrical Distribution Network;2022

5. Improvement of Power Quality in Distribution Grid with Renewable Energy Generation Using DSTATCOM;2021 Innovations in Power and Advanced Computing Technologies (i-PACT);2021-11-27

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