Recursive Kalman Filter for Optoelectronic Systems

Machine Learning Methods in Systems: Proceedings of 13th Computer Science On-line Conference (CSOC 2024). Lecture Notes in Networks and Systems. Vol.1126 2024
Morteza A Sharif, Mehdi Khodavirdizadeh, Vjačeslavs Bobrovs

We develop a modified recursive kalman filter for estimating the dynamical behavior of the nonlinear complex optoelectronic systems. The signal strength is quite fair for the highly noisy measuring data. Moreover, the predicting is quite fast as required for fast optoelectronic phenomena

Keywords
optoelectronic systems; Recursive Kalman filter; Signal to noise ratio
DOI
10.1007/978-3-031-70595-3_10
Hyperlink
https://link.springer.com/chapter/10.1007/978-3-031-70595-3_10

Sharif, M., Khodavirdizadeh, M., Bobrovs, V. Recursive Kalman Filter for Optoelectronic Systems. In: Machine Learning Methods in Systems: Proceedings of 13th Computer Science On-line Conference (CSOC 2024). Lecture Notes in Networks and Systems. Vol.1126, Germany, Berlin, 25-28 April, 2024. Cham: Springer Science and Business Media Deutschland GmbH, 2024, pp.78-82. ISBN 978-303170594-6. ISSN 2367-3370. Available from: doi:10.1007/978-3-031-70595-3_10

Publication language
English (en)