Диссертация (1150597), страница 10
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Í., ×åðâîíåíêèñ À. ß. Òåîðèÿ ðàâíîìåðíîé ñõîäèìîñòè ÷àñòîò ïîÿâëåíèÿ ñîáûòèé ê èõ âåðîÿòíîñòÿì è çàäà÷à ïîèñêàîïòèìàëüíîãî ðåøåíèÿ ïî ýìïèðè÷åñêèì äàííûì // Àâòîìàòèêà èòåëåìåõàíèêà. 1971. 2. C. 4253.[2] Âàïíèê Â. Í. Âîññòàíîâëåíèå çàâèñèìîñòåé ïî ýìïèðè÷åñêèì äàííûì. Ì.: Íàóêà. 1979. 448 c.[3] V.
N. Vapnik. Estimation of Dependencies Based on Empirical Data.SpringerVerlag 1982. 457 p.[4] Ôîìèí Â.Í. Ìàòåìàòè÷åñêàÿ òåîðèÿ îáó÷àåìûõ îïîçíàþùèõ ñèñòåì. Ë.: Èçä-âî Ëåíèíãð. óí-òà. 1976. 236 ñ.[5] Schweppe F.C. Uncertain Dynamic Systems. New York-London:Prentice-Hall. 1973. 563 p.[6] Calaore G, Polyak B. T. Stochastic algorithms for exact andapproximate feasibility of robust LMIs // IEEE Trans. Autom. Control.
2001. Vol. 46. P. 17551759.[7] Ãðàíè÷èí Î. Í., Ïîëÿê Á. Ò. Ðàíäîìèçèðîâàííûå àëãîðèòìûîöåíèâàíèÿ è îïòèìèçàöèè ïðè ïî÷òè ïðîèçâîëüíûõ ïîìåõàõ. 2003. Ì.: Íàóêà. 291 c.[8] Tempo R., Calaore G., Dabbene F. Randomized Algorithms forAnalysis and Control of Uncertain Systems: with Applications. 2013. New York: Springer-Verlag. 337 p.67[9] Granichin O., Volkovich Z., Toledano-Kitai Dvora RandomizedAlgorithms in Automatic Control and Data Mining.
Springer. 2015. 251 p.[10] Ëüþíã Ë., Ñåäåðñòðåì T. Èäåíòèôèêàöèÿ ñèñòåì: òåîðèÿ äëÿïîëüçîâàòåëÿ. Ì.: Hàóêà. 1991. 431 c.[11] Öûïêèí ß.Ç. Èíôîðìàöèîííàÿ òåîðèÿ èäåíòèôèêàöèè. Ì.: Íàóêà. 1995. 336 c.[12] Ôîìèí Â. Í., Ôðàäêîâ À. Ë., ßêóáîâè÷ Â. À. Àäàïòèâíîå óïðàâëåíèå äèíàìè÷åñêèìè îáúåêòàìè. 1981. Ì.: Íàóêà.
448 ñ.[13] Kushner H. J., Yin G. G. Stochastic Approximation Algorithms andApplications. New York. Springer-Verlag. 2003. 497 p.[14] Spall J. S. Introduction to stochastic search and optimization:estimation, simulation, and control. Wiley, Hoboken, NJ. 2003.597 p.[15] Granichin O., Amelina N. Simultaneous perturbation stochasticapproximation for tracking under Unknown but bounded disturbances// IEEE Transactions on Automatic Control. June 2015.
Vol. 60,Is. 6. P. 16531658.[16] GranichinO.,VolkovichV.,Toledano-KitaiD.RandomizedAlgorithms in Automatic Control and Data Mining. SpringerVerlag: Heidelberg New York Dordrecht London. 2015. 251 p.[17] ÔîìèíÂ.Í.Ðåêêóðåíòíîåîöåíèâàíèåèàäàïòèâíàÿôèëüòðàöèÿ. 1984. Ì.: Íàóêà. C. 288.[18] Gasnikov A. V., Dmitriev D. Y. On ecient randomized algorithmsfor nding the PageRank vector // Computational Mathematics andMathematical Physics.
2015. V. 55, 3. C. 349365.68[19] Ljung L. System Identication: Theory for the User // EnglewoodClis. NJ, Prentice Hall. 1999. 609 p.[20] Åìåëüÿíîâ Ñ.Â. Ñèñòåìû àâòîìàòè÷åñêîãî óïðàâëåíèÿ ñ ïåðåìåííîé ñòðóêòóðîé. 1967. Ì.: Íàóêà. 336 ñ.[21] Ãðàíè÷èí Î.Í., Khantuleva T. A. Adapting Wing Elements(Feathers) of an Airplane in a Turbulent Flow with a MultiagentProtocol // Automation and Remote Control. 2017. Vol.
78,10. P. 18671882.[22] Ãðàíè÷èí Î.Í., Khantuleva T. A. Hibrid Systems and RandomizedMeasuring in Nonequilibrium Processes // Dierential Equations andControl Processes. 2004. 3. P. 3543.[23] Ãðàíè÷èí Î. Í., Õàíòóëåâà Ò. À. Àäàïòàöèÿ ýëåìåíòîâ êðûëà(ïåðüåâ) ñàìîëåòà â òóðáóëåíòíîì ïîòîêå ñ ïîìîùüþ ìóëüòèàãåíòíîãî ïðîòîêîëà // Àâòîìàòèêà è òåëåìåõàíèêà.
2017. 10. Ñ. 168188.[24] Ãðàíè÷èí Î. Í., Õàíòóëåâà Ò. À. Ãèáðèäíûå ñèñòåìû è ðàíäîìèçèðîâàííûå èçìåðåíèÿ â íåðàâíîâåñíûõ ïðîöåññàõ // Äèôôåðåíöèàëüíûå óðàâíåíèÿ è ïðîöåññû óïðàâëåíèÿ. 2004. 3. Ñ.3543.[25] Csaji B., Campi M. C., Weyer E. Sign-perturbed sums: A newsystem identication approach for contructing exact non-asymptoticcondence regions in linear regression models // IEEE Trans. on SignalProcessing. 2015. V. 63, 1. P.
169181.[26] Ñåíîâ À. À., Ãðàíè÷èí Î. Í. Èäåíòèôèêàöèÿ ïàðàìåòðîâ ëèíåéíîé ðåãðåññèè ïðè ïðîèçâîëüíûõ âíåøíèõ ïîìåõàõ â íàáëþäåíèÿõ//  ñá. òðóäîâ XII Âñåðîññèéñêîå ñîâåùàíèå ïî ïðîáëåìàì óïðàâëåíèÿ (ÂÑÏÓ-2014), Ðîññèÿ, Ìîñêâà, ÈÏÓ ÐÀÍ, 16-19 èþíÿ 2014. 2014. Ñ. 27082719.69[27] Amelin K., Granichin O. N.
Randomized control strategies underarbitrary external noise // IEEE Transactions on Automatic Control.2016. Vol. 61, 5. P. 13281333.[28] Senov A., Amelin K., Amelina N., Granichin O. Exact condenceregions for linear regression parameter under external arbitrary noise// In: Proc. of the 2014 American Control Conference (ACC), 4-6 June,Portland, USA. 2014. P. 50975102.[29] Ìîðîçîâ Í.Ô., Ïåòðîâ Þ.Â. ¾Êâàíòîâàÿ¿ ïðèðîäà è äâîéñòâåííûéõàðàêòåð ðàçðóøåíèÿ òâåðäûõ òåë // Äîêëàäû Àêàäåìèè íàóê. 2002.
Ò. 382, 2. Ñ. 206-209.[30] Morozov N., Petrov Y. Dynamics of Fracture // Springer-Verlag.Berlin-Heidelberg-New York. 2000. 98 p.[31] Petrov Y. V., Utkin A. A. Dependence of the dynamic strength onloading rate // Mater. Science. 1989. Vol. 25, 2.
P. 153156.[32] Petrov Y. V. Incubation time criterion and the pulsed strength ofcontinua: Fracture, cavitation, and electrical breakdown // DokladyPhysics. 2004. Vol.49, 4. P. 246-249.[33] Ôåëüäáàóì À. À. Î ïðîáëåìàõ äóàëüíîãî óïðàâëåíèÿ //  êí.: Ìåòîäû îïòèìèçàöèè àâòîìàòè÷åñêèõ ñèñòåì. Ì.: Íàóêà. 1972. c.89108.[34] Âîëêîâà Ì.Â., Ãðàíè÷èí Î.Í., Âîëêîâ Ã.À., Ïåòðîâ Þ.Â. Î âîçìîæíîñòè ïðèìåíåíèÿ ìåòîäà çíàêî-âîçìóùåííûõ ñóìì äëÿ îáðàáîòêè ðåçóëüòàòîâ äèíàìè÷åñêèõ èñïûòàíèé // Âåñòíèê ÑÏáÃÓ. 2018. Ñåð. 1. Òîì 63. Âûï. 1. Ñ. 3040.[35] Volkova M.V., Granichin, Petrov Y.V., Volkov G.A. Dynamic fracturetests data treatment based on the randomized approach // Advancesin Systems Science and Applications (ASSA). 2017.
. 3. P.3543.70[36] Volkova M., Granichin O., Petrov Yu., Volkov G. Sign-perturbed sumsapproach for data treatment of dynamic fracture tests // In: Proc. ofthe 56th IEEE Conference on Decision and Control, December 12-15,2017, Melbourne, Australia. 2017. P. 16521656.[37] Âîëêîâà Ì. Â., Ãðàíè÷èí Î. Í. Ìèíèìèçàöèÿ ôóíêöèîíàëà òèïà ñðåäíåãî ðèñêà íà îñíîâå êîíå÷íîãî (âîçìîæíî ìàëîãî) íàáîðàýêñïåðèìåíòàëüíûõ äàííûõ // Ñòîõàñòè÷åñêàÿ îïòèìèçàöèÿ â èíôîðìàòèêå. 2018. Ò. 13, Âûï.
2. Ñ. 335.[38] Volkova M. One method to solve a problem of nonlinear two-stageperspective stochastic planning // International Journal of Pure andApplied Mathematics. 2017. V. 112, 4. P. 817826.[39] Êîëáèí Â. Â., Ñâèùèêîâà Ì. Â. Îäèí ïðÿìîé ìåòîä ñòîõàñòè÷åñêîé îïòèìèçàöèè // Èçâåñòèÿ Ñàðàòîâñêîãî Óíèâåðñèòåòà.
Íîâàÿñåðèÿ. Ñåðèÿ: Ìàòåìàòèêà. Ìåõàíèêà. Èíôîðìàòèêà, 2012. T. 12,4. Ñ. 1114.[40] Âîëêîâà Ì. Â., Ìèõååâ Ñ. Å., Ìîðîçîâ Ï. Ä. Êîððåëÿöèÿ äèíàìèêè âíóòðåííåãî âàëîâîãî ïðîäóêòà ñ öåíîé ìîòîðíîãî òîïëèâà //Ìîëîäîé ó÷åíûé. 2017. 11(145). Ñ. 192198.[41] Ñâèùèêîâà Ì. Â. Îäèí ìåòîä ïðîãíîçèðîâàíèÿ ÂÂÏ Ðîññèè //Ïðîöåññû óïðàâëåíèÿ è óñòîé÷èâîñòü: Òðóäû 42-é ìåæäóíàðîäíîéíàó÷íîé êîíôåðåíöèè àñïèðàíòîâ è ñòóäåíòîâ.
2011. Ñ. 550554.[42] Svishchikova M. V. One problem of nonlilear stochastic programming// International Journal of Applied Mathematics and Statistics. 2014. V. 52, 7. P. 1-7.[43] Ñâèùèêîâà Ì. Â. Ðåøåíèå îäíîé äâóõýòàïíîé çàäà÷è íåëèíåéíîãî ñòîõàñòè÷åñêîãî ïðîãðàììèðîâàíèÿ // Èííîâàöèè â íàóêå. 2014. 3(28). Ñ.
1222.71[44] Ñâèùèêîâà Ì. Â. Îäèí ñïîñîá ðåøåíèÿ çàäà÷ ñòîõàñòè÷åñêîãîïðîãðàììèðîâàíèÿ ñïåöèàëüíîãî âèäà // Ïðîöåññû óïðàâëåíèÿ èóñòîé÷èâîñòü: Òðóäû 43-é ìåæäóíàðîäíîé íàó÷íîé êîíôåðåíöèè.2012. Ñ. 559563.[45] Ïðèñòàâêî Â. Ò., Ñâèùèêîâà Ì. Â. Êîäèðîâàíèå è äåêîäèðîâàíèåâåêòîðíûõ ãàóññîâñêèõ ñèãíàëîâ // Ïðîöåññû óïðàâëåíèÿ è óñòîé÷èâîñòü: Òðóäû 41-é ìåæäóíàðîäíîé íàó÷íîé êîíôåðåíöèè àñïèðàíòîâ è ñòóäåíòîâ. 2010. Ñ. 692698.[46] Ïðèñòàâêî Â.Ò., Ñâèùèêîâà Ì.Â. Ëèïèäíîñòü ñóáúåêòà // Ïðîöåññû óïðàâëåíèÿ è óñòîé÷èâîñòü: Òðóäû 40-é ìåæäóíàðîäíîé íàó÷íîé êîíôåðåíöèè àñïèðàíòîâ è ñòóäåíòîâ. 2009. Ñ.
656658.[47] Bai E. W., Nagpal K. M., Tempo R. Bounded-error parameterestimation: Noise models and recursive algorithms // Automatica. 1996. Vol. 32. 7. P. 985999.[48] ÏîëÿêÁ.Ò.,ÙåðáàêîâÏ.Ñ.Ðîáàñòíàÿóñòîé÷èâîñòüèóïðàâëåíèå. Ì.: Íàóêà. 2002. 303 ñ.[49] Ïîëÿê Á.Ò., Õëåáíèêîâ Ì.Â., Ùåðáàêîâ Ï.Ñ. Óïðàâëåíèå ëèíåéíûìè ñèñòåìàìè ïðè âíåøíèõ âîçìóùåíèÿõ. Òåõíèêà ëèíåéíûõ ìàòðè÷íûõ íåðàâåíñòâ. Ì.: ËÅÍÀÍÄ. 2014. 560 ñ.[50] Ñîêîëîâ Â.Ô. Îöåíêà êà÷åñòâà ðîáàñòíîé ñèñòåìû óïðàâëåíèÿ ïðèíåèçâåñòíûõ âåðõíèõ ãðàíèöàõ âîçìóùåíèé è ïîìåõè èçìåðåíèé //Àâòîìàòèêà è òåëåìåõàíèêà.
2010. 9. Ñ. 318.[51] Ãðàíè÷èí Î. Í., Ôîìèí Â. Í. Àäàïòèâíîå óïðàâëåíèå ñ èñïîëüçîâàíèåì ïðîáíûõ ñèãíàëîâ // Àâòîìàòèêà è òåëåìåõàíèêà. 1986. 2. C. 100112.[52] Ãðàíè÷èí Î. Í. Îá îäíîé ñòîõàñòè÷åñêîé ðåêóððåíòíîé ïðîöåäóðå ïðè çàâèñèìûõ ïîìåõàõ â íàáëþäåíèè, èñïîëüçóþùåé íà âõîäå72ïðîáíûå âîçìóùåíèÿ // Âåñòíèê Ëåíèíãðàäñêîãî óíèâåðñèòåòà. 1989. Ñåð. 1, Âûï. 1, 1.
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