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 Выпуск 50
- Kustov A. Anisotropy-based analysis for case of nonzero-mean input disturbance
In the created in the 90th anisotropy-based control theory the sequence of Gaussian random vectors with zero mean and certain mean anisotropy level was accepted as input perturbations acting on a linear system. This paper introduces the concepts of mean anisotropy of the sequence with nonzero mean and anisotropic norm of the system with given input. The problem of anisotropy-based analysis in frequency domain is considered and the difference is shown between classical formulas for computing mean anisotropy and anisotropic norm under the zero mean and the new formulas.
- Yurchenkov A. Anisotropic robust regulator synthesis for structured uncertainty control model
A problem of anisotropic control synthesis is considered and solved for the model of a control plant containing structured uncertainty. Adding a fictive input reduces the problem to the one of H1-optimization. The suggested numerical algorithm uses the homotopy method to calculate matrices of an anisotropic regulator basing on an H2-regulator. The designed regulator and the standard regulator for an unstructured uncertainty model are compared. Computer simulation shows advantages of the proposed regulator
- Chernykh N. Implicit strong methods for the numerical solution modelling for stochastic differential equations with markovian switching
We study implicit strong approximate methods for stochastic differential equations with Markovian switching (SDEwMSs). Theoretical results are verified with numerical examples in Scilab framework.
- Chesnokov A. Columns-based intelligent systems under incomplete information
The paper considers columns-based intelligent systems working under incomplete information, when only a part of the whole input image is received. We provide solutions to both direct and inverse problems. We also reveal the relation between system’s ability to work under incomplete information and predicting ability of the system.
- Bakhitova R., Lakman I., Akhmetshina G. Panel modeling of production output in russian regions
We use panel modeling to build a production function for 79 Russian regions. Under a fixed effect model we split regions into four groups and perform similarity analysis of regions sharing the same group.
- Topinsky V. Reserve price efficiency and competitive pressure in auctions
In this paper I analyze the reserve price efficacy of an auction, that is the relative value of the expected revenue increase induced by the optimal reserve price. I define the competitive
pressure in an auction and the notion of one auction dominance over another auction in terms of competition level. After that I prove that the reserve price efficacy decays with respect to the increase of competition level. Finally I provide some examples of auction attributes, which monotonically affect the competition level.
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