Adaptive linear combiners a robust neural network technique for on-line harmonic tracking

被引：0

作者：

Zouidi, Abdelaziz ^{[1
]}

Fnaiech, Farhat ^{[1
]}

AL-Haddad, Kamal ^{[2
]}

Rahmani, Salem ^{[1
]}

机构：

[1] Univ Tunis, Ecole Super Sci & Tech Tunis, Equipe Rech SICISI, 5 Av Taha Hussein, Tunis 1008, Tunisia

[2] Ecole Technol Super, CRC, ECPE, Quebec City H3C 1K3, PQ, Canada

来源：

IECON 2008: 34TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, VOLS 1-5, PROCEEDINGS | 2008年

关键词：

selective harmonic detection; artificial intelligence; artificial neural networks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Intelligent techniques of harmonic detection or estimation are nowadays of a great interest in power system applications, their ability to deal with high non-linearities attract researchers to investigate the performance of these methods mainly based on artificial intelligence namely using artificial neural networks (ANNs). In the literature many harmonic detection or estimation methods were presented, in this paper we focus on adaptive linear neuron (ADALINE) to estimate the fundamental component and selected harmonic content of a distorted signal compared to the fast Fourier transformation (FFT) algorithm.

引用

页码：479 / +

页数：2

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