Fast non-recursive extraction of individual harmonics using artificial neural networks

Wijayakulasooriya, Janaka V., Putrus, Ghanim and Ng, Chong (2005) Fast non-recursive extraction of individual harmonics using artificial neural networks. IEE Proceedings: Generation, Transmission and Distribution, 152 (4). p. 539. ISSN 1350-2360

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Official URL: http://dx.doi.org/10.1049/ip-gtd:20045089

Abstract

A collaborative work between Northumbria University and University of Peradeniya (Sri Lanka). It presents a novel technique based on Artificial Neural Networks for fast extraction of individual harmonic components. The technique was tested on a real-time hardware platform and results obtained showed that it is significantly faster and less computationally complex than other techniques. The paper complements other publications by the author (see paper 1) on the important area of “Power Quality” of electric power networks. It involves the application of advanced techniques in artificial intelligence to solve power systems problems.

Item Type: Article
Uncontrolled Keywords: Neural networks (Computer science), Harmonic analyzers
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics and Information Sciences
Depositing User: EPrint Services
Date Deposited: 26 Nov 2008 15:03
Last Modified: 10 May 2017 15:30
URI: http://nrl.northumbria.ac.uk/id/eprint/2799

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