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Reseach Article

Removal of Harmonics from the output of Buck Converter by Hetero-associative Neural Network

by Moumi Pandit, Mousumi Gupta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 6
Year of Publication: 2012
Authors: Moumi Pandit, Mousumi Gupta
10.5120/6781-9080

Moumi Pandit, Mousumi Gupta . Removal of Harmonics from the output of Buck Converter by Hetero-associative Neural Network. International Journal of Computer Applications. 45, 6 ( May 2012), 1-4. DOI=10.5120/6781-9080

@article{ 10.5120/6781-9080,
author = { Moumi Pandit, Mousumi Gupta },
title = { Removal of Harmonics from the output of Buck Converter by Hetero-associative Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 6 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number6/6781-9080/ },
doi = { 10.5120/6781-9080 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:36:51.722895+05:30
%A Moumi Pandit
%A Mousumi Gupta
%T Removal of Harmonics from the output of Buck Converter by Hetero-associative Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 6
%P 1-4
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In almost all applications of power electronics there is always an influence of harmonics and noise in voltage and current waveforms. In this paper, a harmonic rejection technique has been proposed based on neural network platform. An ANN model has been developed which when trained can remove harmonics from the output of the buck converter. In this paper, a buck converter has been designed in MATLAB environment and the output voltage waveform is corrupted with harmonics. The corrupted output voltage is then passed through an ANN model. The developed model will remove the harmonics by hetero associative neural network approach. In the whole process a buck converter is simulated, one ANN model is developed, which is trained and tested on MATLAB platform.

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Index Terms

Computer Science
Information Sciences

Keywords

Buck Converter Harmonic Noise Hetero Associative Neural Network Target Detection Filter Design