Abstract
The paper presents a methodology for the synthesis of systems for monitoring the state of a high-speed fiber-optical linear path, based on the information and measuring control system that implements neural network recognition algorithms with synthesis by dominance. The proposed information-measuring system processes levels of the average intensity of the optical signal received at various carriers in a certain retrospective over a defined period of time. Neural network algorithms are synthesized by optimizing the parameters of a neural network that allow to make a conclusion about the state of a high-speed fiber-optical linear path.
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Acknowledgment
This work is partially supported by the Russian Foundation for Basic Research (grant No. 16-08-00696-a) and the Council for Grants of the President of Russia (Projects No. MК-7925.2016.9).
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Saitov, I.A., Basov, O.O., Motienko, A.I., Saitov, S.I., Bizin, M.M., Budkov, V.Y. (2016). Neural Network System for Monitoring State of a High-Speed Fiber-Optical Linear Path. In: Cheng, L., Liu, Q., Ronzhin, A. (eds) Advances in Neural Networks – ISNN 2016. ISNN 2016. Lecture Notes in Computer Science(), vol 9719. Springer, Cham. https://doi.org/10.1007/978-3-319-40663-3_57
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DOI: https://doi.org/10.1007/978-3-319-40663-3_57
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