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Neural Network Based High Accuracy Frequency Harmonic Analysis in Power System.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Derong Liu
Shumin Fei
Zengguang Hou
Huaguang Zhang
Changyin Sun
Source :
Advances in Neural Networks: ISNN 2007 (9783540723943); 2007, p1006-1014, 9p
Publication Year :
2007

Abstract

A back-propagation neural network method is proposed for accurate frequencies, amplitudes and phases estimation from periodic signals in power systems, and the convergence theorem shows that the proposed algorithm can be convergent asymptotically to its global minimum. The method is aimed at the system in which the sampling frequency cannot be locked on the actual fundamental frequency. Some simulating examples are given and the results show that the accuracy of the estimates provided by the proposed approach in the asynchronous case is relatively better than that of the estimates obtained with the conventional harmonic analysis methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540723943
Database :
Complementary Index
Journal :
Advances in Neural Networks: ISNN 2007 (9783540723943)
Publication Type :
Book
Accession number :
33155097
Full Text :
https://doi.org/10.1007/978-3-540-72395-0_123