This article is cited 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.

Presented by the member of Editorial Board: A. I. Kibzun

Received: 27.03.2013

 English version: Automation and Remote Control, 2014, 75:5, 872–879

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