Empirical Formulas for Estimation of Rice Distribution Parameters
https://doi.org/10.15514/ISPRAS-2026-38(3)-18
Abstract
The Rice distribution is applied as a mathematical model in the study of various problems in science and technology. The main task in applications is to estimate the parameters of the Rice distribution from a sample of the measured signal and to separate the parameters of the deterministic signal and noise based on these estimates. Parameter estimation is mainly performed using the maximum likelihood method and the method of moments. However, as is known, both methods often lead to solving systems of equations containing special functions, so additional computational resources are used for the solution. One of the methods to overcome these difficulties is the development of simple, yet sufficiently effective empirical formulas (EFs) that are competitive in accuracy with known algorithms for estimating the parameters of the Rice distribution. This work is devoted to solving this problem.
About the Authors
David ASATRYAN
Institute for Informatics and Automation Problems of NAS RA, Russian-Armenian University
Armenia
Armenia
Dr. Sci. (Tech.), Prof., Lead Researcher, Department of Digital Signal and Image Processing, Institute of Computer Science and Automation Problems, NAN RA since 2002. Area of research interests: digital processing of signals and images, statistical methods of data analysis, methods of estimation of parameters of distributions.
Liana ANDREASYAN
National Polytechnic University of Armenia
Armenia
Armenia
Cand. Sci. (Tech.), associate professor at the Institute of Information and Telecommunication Technologies and Electronics of the National Polytechnic University of Armenia. Research interests: statistical signal processing, Rice distribution, methods for estimating distribution parameters, medical image processing.
Grigor SAZHUMYAN
Institute for Informatics and Automation Problems of NAS RA, Russian-Armenian University
Armenia
Armenia
Researcher at the Laboratory of Digital Signal and Image Processing of the Institute for Informatics and Automation Problems of NAS RA. Research interests: digital image processing, statistical distributions, machine learning methods in image analysis.
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Review
For citations:
ASATRYAN D., ANDREASYAN L., SAZHUMYAN G. Empirical Formulas for Estimation of Rice Distribution Parameters. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2026;38(3):7-14. (In Russ.) https://doi.org/10.15514/ISPRAS-2026-38(3)-18
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