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Optical Engineering

Method of forecasting energy center positions of laser beam spot images using a parallel hierarchical network for optical communication systems
Author(s): Leonid I. Timchenko; Natalia I. Kokryatskaya; Viktor V. Melnikov; Galina L. Kosenko
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Paper Abstract

A forecasting method, based on the parallel-hierarchical (PH) network and hyperbolic smoothing of empirical data, is presented in this paper. Preceding values of the time series, hyperbolic smoothing, and PH network data are used for forecasting. To determine a position of the next route fragment in relation to X and Y axes, hyperbola parameters are sent to the route parameter forecasting system. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the PH network. An average prediction error is 0.55% for the developed method and 1.62% for neural networks. That is why, due to the use of the PH network and hyperbolic smoothing, the developed method is more efficient for real-time systems than traditional neural networks in forecasting energy center positions of laser beam spot images for optical communication systems.

Paper Details

Date Published: 9 May 2013
PDF: 10 pages
Opt. Eng. 52(5) 055003 doi: 10.1117/1.OE.52.5.055003
Published in: Optical Engineering Volume 52, Issue 5
Show Author Affiliations
Leonid I. Timchenko, Kiev Univ. of Economy and Transport Technology (Ukraine)
Natalia I. Kokryatskaya, Kiev Univ. of Economy and Transport Technology (Ukraine)
Viktor V. Melnikov, Kiev Univ. of Economy and Transport Technology (Ukraine)
Galina L. Kosenko, Kiev Univ. of Economy and Transport Technology (Ukraine)


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