Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)


For citation:

Faizullin R. T., Faizullin R. R. The restoration of functional relationships with a given singularity. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2014, vol. 14, iss. 1, pp. 103-108. DOI: 10.18500/1816-9791-2014-14-1-103-108, EDN: SCSSUN

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
25.03.2014
Full text:
(downloads: 160)
Language: 
Russian
Heading: 
UDC: 
519.654
EDN: 
SCSSUN

The restoration of functional relationships with a given singularity

Autors: 
Faizullin Rashit Tagirovich, Omskij filial Instituta matematiki SO RAN
Faizullin Ramil Rashitovich, Omskij filial Instituta matematiki SO RAN
Abstract: 

 Provided methods recovery of functional dependence with a specified discontinuity. Application of the algorithm of building function with given discontinuity is shown. The first method is based on a formal function minimization by random search. The second uses the information content of the data. 

References: 
  1. Musatov M. V., L’vov A. A. Model Analysis of the Least Squares Method and Methods to Obtain Estimates. Vestnik Saratovskogo gosudarstvennogo tehnicheskogo universiteta [Bulletin of the Saratov State Technical University], 2009, vol. 4, no. 2c, pp. 137–140 (in Russian).
  2. Kvetnoj R. N., Bojko A. R., Stepova T. A. A Multivariate Polynomial Approximation of the Dependencies of the Specified Array of Interval Data on Method Least Squares. Visnik Vinnic’kogo politehnichnogo institutu [Bulletin of Vinnica Polytechnical Institute], 2011, no. 3, pp.103–106 (in Russian).
  3. Dzhagarov Ju. A. Programmnyj modul’ dlja rascheta approksimirujushhih polinomov po metodu naimen’shih kvadratov [The Software Module for the Calculation of Approximating Polynomials by the Method of Least Squares]. Programmnye produkty i sistemy [Program products and systems], 2005, no. 3, pp. 14 (in Russian).
  4. Suhanov D. Ja., Suhanov A. Ja. The Method of Iterative Tuning Multilayer Neural Network Based on the Method of Least Squares. Doklady Tomskogo gosudarstvennogo universiteta sistem upravlenija i radiojelektroniki [Reports of Tomsk State University of Control Systems and Radio Electronics], 2004, no. 2, pp. 111–115 (in Russian).
  5. Milov V. R. Adaptive Signal Processing Based on Recursive Algorithm with Regularization of the Least Squares. Izvestija vysshih uchebnyh zavedenij. Priborostroenie, 2003, vol. 46, no. 10, pp. 11–17 (in Russian).
  6. Tao Huasjue, Juj Shenven’, Li Pin. A New Model for the Solution of the Equalization Method of Nonlinear Dynamic Least Squares. Gornyj informacionnoanaliticheskij bjulleten’ (nauchno-tehnicheskij zhurnal) [Mining informational and analytical bulletin (scientific and technical journal)], 2001, no. 7, pp. 157–160 (in Russian).
  7. Brammer K., Ziffling G. Fil’tr Kalmana–B’jusi [Kalman-Bucy filter]. Moscow, Nauka, 1982 (in Russian).
  8. Ageev A. L., Antonova T. V. Localization of Discontinuities of the First Kind for the Functions with Bounded Variation. Tr. IMM UrO RAN [Proc. of the IMM of Ural department of RAS], 2012, vol. 18, no. 1, pp. 56–68 (in Russian).
  9. Loginov K. V., Myznikov A. M., Fajzullin R. T. Calculation, optimization and control modes of the large hydraulic networks. Matem. modelirovanie [Math. modeling], 2006, vol. 18, iss. 9, pp. 92–106 (in Russian
Received: 
12.08.2013
Accepted: 
15.01.2014
Published: 
28.02.2014
Short text (in English):
(downloads: 158)