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Avtomatika i Telemekhanika, 2014, Issue 5, Pages 83–90
(Mi at9095)
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This article is cited in 3 scientific papers (total in 3 papers)
Stochastic Systems, Queuing Systems
Estimating the characteristics of randomized dynamic data models (the entropy-robust approach)
Yu. S. Popkov, A. Yu. Popkov, Yu. N. Lysak Institute for Systems Analysis, Russian Academy of Sciences, Moscow, Russia
Abstract:
We propose a new approach to finding dependencies between small volumes of input and output data based on randomized dynamic models and density estimation for the distributions of their parameters. Randomized dynamic models are defined by functional Volterra polynomials. To construct robust nonparametric estimation procedures, we develop an entropybased approach that employs functionals of generalized informational Boltzmann and Fermi entropies.
Citation:
Yu. S. Popkov, A. Yu. Popkov, Yu. N. Lysak, “Estimating the characteristics of randomized dynamic data models (the entropy-robust approach)”, Avtomat. i Telemekh., 2014, no. 5, 83–90; Autom. Remote Control, 75:5 (2014), 872–879
Linking options:
https://www.mathnet.ru/eng/at9095 https://www.mathnet.ru/eng/at/y2014/i5/p83
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Statistics & downloads: |
Abstract page: | 317 | Full-text PDF : | 62 | References: | 41 | First page: | 22 |
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