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Predictive Harmonic Cancellation Using Neural Networks

Title: Predictive Harmonic Cancellation Using Neural Networks.
Name(s): Malinconico, Brian, author
Foo, Simon, professor directing thesis
Roberts, Rodney, committee member
Meyer-Baese, Anke, committee member
Department of Electrical and Computer Engineering, degree granting department
Florida State University, degree granting institution
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2010
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: Filtering is an important aspect of the modern power system. By reducing the effects of harmonics, power transmission and utilization becomes more efficient. This research examines the use of neural networks for the estimation and prediction of harmonics. The utilization of neural networks for adaptive harmonic prediction, allows the cancellation of harmonics before their creation. A large part of this research focuses on the estimation of Fourier coefficients. By identifying the strengths and weaknesses of neural networks for Fourier coefficient estimation future direction for research was determined. The deficiencies of the developed networks prevent the application of this system in real-life situations. Despite the need for future research, the performance of the neural networks shows significant possibilities.
Identifier: FSU_migr_etd-2770 (IID)
Submitted Note: A Thesis submitted to the Department of Electrical & Computer Engineering in partial fulfillment of the requirements for the degree of Master of Electrical Engineering.
Degree Awarded: Fall Semester, 2010.
Date of Defense: October 15, 2009.
Keywords: artificial intelligence, power systems, harmonics, neural networks
Bibliography Note: Includes bibliographical references.
Advisory Committee: Simon Foo, Professor Directing Thesis; Rodney Roberts, Committee Member; Anke Meyer-Baese, Committee Member.
Subject(s): Electrical engineering
Computer engineering
Persistent Link to This Record:
Owner Institution: FSU

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Malinconico, B. (2010). Predictive Harmonic Cancellation Using Neural Networks. Retrieved from