By Topic

Neural Compensation for a Microcontroller Based Frequency Synthesizer-Vector Voltmeter

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Amitava Chatterjee ; Electrical Engineering Department, Jadavpur University, Kolkata, India ; Gautam Sarkar ; Anjan Rakshit

An automated neural network compensation scheme is proposed for an indigenously developed microcontroller based frequency synthesizer-vector voltmeter system, developed using direct digital synthesis and the synchronous detection technique. This compensator, when implemented online, can significantly improve the reading of an unknown voltage (both in magnitude and phase), in real-time. The neural compensator developed is trained offline on the basis of real data acquired from the system, and when this compensator is implemented online, it could outperform polynomial and fuzzy based compensators for a variety of different unknown voltages under measurement.

Published in:

IEEE Sensors Journal  (Volume:11 ,  Issue: 6 )