A Resilient Backpropagation Neural Network based Phase Correction System for Automatic Digital AC Bridges

Author

Dutta, M. ; Cbatterjee, A. ; Rakshit, A.

Author_Institution

Dept. of Electr. Eng., Jadavpur Univ., Kolkata

fYear

2004

fDate

38139

Firstpage

374

Lastpage

375

Abstract

The present paper describes the development of an ANN based phase correction system which has been employed in conjunction with a real automatic digital ac bridge. The proposed ANN-based phase corrector has been developed using backpropagation learning employing resilient backpropagation (popularly known as RPROP). Significant improvements have been obtained in the proposed phase correction system for measuring impedance and reported in the paper

Keywords

backpropagation; electric impedance measurement; neural nets; automatic digital AC bridges; backpropagation neural network; impedance measurement; phase correction system; Artificial neural networks; Backpropagation; Bridge circuits; Frequency estimation; Impedance measurement; Instruments; Least squares approximation; Neural networks; Phase measurement; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Precision Electromagnetic Measurements Digest, 2004 Conference on

Conference_Location

London

Print_ISBN

0-7803-8494-6

Electronic_ISBN

0-7803-8494-6

Type

conf

DOI

10.1109/CPEM.2004.305621

Filename

4097276

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3447546