Recurrent Algorithms of Structural Classification Analysis for Complex Organized Information

 
PIIS000523100001876-7-1
DOI10.31857/S000523100001876-7
Publication type Article
Status Published
Authors
Affiliation: Markov Processes International
Address: United States, New-York
Affiliation: Markov Processes International
Address: United States, New-York
Affiliation: Trapeznikov Institute of Control Sciences, Russian Academy of Sciences
Address: Russian Federation, Moscow
Affiliation: Trapeznikov Institute of Control Sciences, Russian Academy of Sciences
Address: Russian Federation, Moscow
Journal nameAvtomatika i Telemekhanika
EditionIssue 10
Pages143-153
Abstract

               

Keywords
Received21.10.2018
Publication date25.10.2018
Number of characters705
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1. Dorofeyuk A.A., Dorofeyuk Yu.A., Pokrovskaya I.V., Chernyavskij A.L. Rekurrentnye algoritmy intellektual'nogo analiza informatsii v slozhnykh izmeritel'no-upravlyayuschikh sistemakh // Datchiki i sistemy. 2016. № 12. S. 3–10.

2. Robbins N., Monro S. A stochastic approximation method // Ann. Math. Stat. 1951. V. 22. No. 1. P. 400–407.

3. Kiefer J., Wolfowitz J. Stochastic Estimation of the Maximum of a Regression Function // Ann. Math. Statist. 1952. V. 23. No. 3. P. 462–466.

4. Nevel'son M.B., Khas'minskij R.Z. Stokhasticheskaya approksimatsiya i rekurrentnoe otsenivanie. M.: Nauka, 1972.

5. Bharath B., S Borkar V. Stochastic approximation algorithms: Overview and recent trends // Sadhana. 1999. No. 24. P. 425–452.

6. Kushner H., Yin G. Stochastic Approximation and Recursive Algorithms and Applications / Ser. “Stochastic Modelling and Applied Probability”. V. 35. N.Y.: Springer-Verlag, 2003.

7. Tsypkin Ya.3., Kel'mans G.K. Rekurrentnye algoritmy samoobucheniya // Tekhnicheskaya kibernetika. 1967. № 5. C. 78–87.

8. Braverman Eh.M., Muchnik I.B. Strukturnye metody obrabotki ehmpiricheskikh dannykh. M.: Nauka, 1983.

9. Braverman Eh.M., Dorofeyuk A.A., Lumel'skij V.Ya., Muchnik I.B. Diagonalizatsiya matritsy svyazi i vydelenie skrytykh faktorov / Problemy rasshireniya vozmozhnostej avtomatov. Vyp. 1. M.: IAT, 1971.

10. Pokrovskaya I.V., Gol'dovskaya M.D., Dorofeyuk Yu.A., Kiselyova N.E. Metody intellektual'noj obrabotki kachestvennykh dannykh // Mashinnoe obuchenie i analiz dannykh. 2014. T. 1. № 10. C. 1396–1406.

11. Bauman E.V., Dorofeyuk A.A., Dorofeyuk Yu.A., Pokrovskaya I.V. Strukturnoklassifikatsionnye metody v zadache identifikatsii slozhnykh ob'ektov upravleniya / Upravlenie razvitiem krupnomasshtabnykh sistem (MLSD’2011): Materialy Pyatoj mezhdunar. konf. T. II. M.: IPU RAN, 2011. 152

12. Bezdek J.C. Pattern Recognition with Fuzzy Objective Function Algorithms. N.Y.: Springer, 1981.

13. Kiseleva N.E., Dorofeyuk A.A., Dorofeyuk Yu.A., Pokrovskaya I.V. Programmno algoritmicheskij kompleks intellektual'nogo analiza slabo formalizovannykh dannykh // Datchiki i sistemy. 2014. № 6. C. 48–53.

14. Spiro A.G., Dorofeyuk A.A., Dorofeyuk Yu.A., Alperovich Eug., Alperovich M. Prognozirovanie diapazona kolebanij tsen aktsij na fondovom rynke // Mater. 8-j Mezhdunar. konf. ≪Upravlenie razvitiem krupnomasshtabnykh sistem≫ (MLSD’2015, Moskva). M.: IPU RAN, 2015. T. 2. S. 388–390.

15. Guchuk V.V., Desova A.A., Dorofeyuk A.A., Anokhin A.M. Protsedura ob'ektivizatsii ehkspertnoj klassifikatsii kharakteristik biosignalov dlya mediko-diagnosticheskikh kompleksov // Datchiki i sistemy. 2014. № 2. S. 2–7.

16. Kuznetsov E.N., Anashkina A.A., Esipova N.G., Tumanyan V.G. Klaster-analiz aminokislotnykh ostatkov belkov na osnove struktury ikh prostranstvennykh kontaktov s nukleotidami DNK // Mater. 8-j Mezhdunar. konf. ≪Upravlenie razvitiem krupnomasshtabnykh sistem≫ (MLSD’2015, Moskva). M.: IPU RAN, 2015. T. 2. S. 382–385.

17. Dorofeyuk Yu.A., Dorofeyuk A.A., Chernyavskij A.L. Metod intellektual'nogo analiza otsenok parametrov monitoringa krupnomasshtabnykh sotsial'no-ehkonomicheskikh sistem dlya nereprezentativnykh vyborok // Mater. 8-j Mezhdunar. konf. ≪Upravlenie razvitiem krupnomasshtabnykh sistem≫ (MLSD’2015, Moskva). M.: IPU RAN, 2015. T. 2. S. 372–375.

18. Mandel A., Bordukov D., Dorofeyuk A., Dorofeyuk J., Chernyavsky A. A Structural Prediction Concept for PlaceNameplaceRailway PlaceTypeState Forecasting Problem // 15 IFAC Sympos. Inform. Control Probl. Manufactur. (INCOM 2015). IFAC–PapersOnLine. V. 48. No. 3. Canada: Ottawa Elsevier, 2015. P. 1338–1342.

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