Method of forecasting energy center positions of laser beam spot images using a parallel hierarchical network for optical communication systems

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...

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Bibliographic Details
Published in:Optical engineering 2013-05, Vol.52 (5), p.055003-055003
Main Authors: Timchenko, Leonid I, Kokryatskaya, Natalia I, Melnikov, Viktor V, Kosenko, Galina L
Format: Article
Language:English
Subjects:
Computer networks
Forecasting
Networks
Neural networks
Optical communication
Smoothing
Spots
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Summary: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.
ISSN:0091-3286
1560-2303
DOI:10.1117/1.OE.52.5.055003