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Discrete-Time Minimum Tracking Based on Stochastic Approximation Algorithm With Randomized Differences. / Granichin, O.; Gurevich, L.; Vakhitov, A.

PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009). IEEE Canada, 2009. p. 5763-5767 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Harvard

Granichin, O, Gurevich, L & Vakhitov, A 2009, Discrete-Time Minimum Tracking Based on Stochastic Approximation Algorithm With Randomized Differences. in PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009). Proceedings of the IEEE Conference on Decision and Control, IEEE Canada, pp. 5763-5767, Joint 48th IEEE Conference on Decision and Control (CDC) / 28th Chinese Control Conference (CCC), Shanghai, 15/12/09. https://doi.org/10.1109/CDC.2009.5400839, https://doi.org/10.1109/CDC.2009.5400839

APA

Granichin, O., Gurevich, L., & Vakhitov, A. (2009). Discrete-Time Minimum Tracking Based on Stochastic Approximation Algorithm With Randomized Differences. In PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009) (pp. 5763-5767). (Proceedings of the IEEE Conference on Decision and Control). IEEE Canada. https://doi.org/10.1109/CDC.2009.5400839, https://doi.org/10.1109/CDC.2009.5400839

Vancouver

Granichin O, Gurevich L, Vakhitov A. Discrete-Time Minimum Tracking Based on Stochastic Approximation Algorithm With Randomized Differences. In PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009). IEEE Canada. 2009. p. 5763-5767. (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2009.5400839, https://doi.org/10.1109/CDC.2009.5400839

Author

Granichin, O. ; Gurevich, L. ; Vakhitov, A. / Discrete-Time Minimum Tracking Based on Stochastic Approximation Algorithm With Randomized Differences. PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009). IEEE Canada, 2009. pp. 5763-5767 (Proceedings of the IEEE Conference on Decision and Control).

BibTeX

@inproceedings{3c0fb883ceff4853ae572c1878a5f70e,
title = "Discrete-Time Minimum Tracking Based on Stochastic Approximation Algorithm With Randomized Differences",
abstract = "In this paper application of the stochastic approximation algorithm with randomized differences to the minimum tracking problem for the non-constrained optimization is considered. The upper bound of mean-squared estimation error is derived in the case of once differentiable functional and almost arbitrary observation noise. Numerical simulation of the estimates stabilization for the multidimensional optimization with unknown but bounded deterministic noise is provided. Stabilization bound has sufficiently small level comparing to significant level of noise.",
keywords = "NOISE",
author = "O. Granichin and L. Gurevich and A. Vakhitov",
year = "2009",
doi = "10.1109/CDC.2009.5400839",
language = "Английский",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "IEEE Canada",
pages = "5763--5767",
booktitle = "PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009)",
address = "Канада",
note = "null ; Conference date: 15-12-2009 Through 18-12-2009",

}

RIS

TY - GEN

T1 - Discrete-Time Minimum Tracking Based on Stochastic Approximation Algorithm With Randomized Differences

AU - Granichin, O.

AU - Gurevich, L.

AU - Vakhitov, A.

PY - 2009

Y1 - 2009

N2 - In this paper application of the stochastic approximation algorithm with randomized differences to the minimum tracking problem for the non-constrained optimization is considered. The upper bound of mean-squared estimation error is derived in the case of once differentiable functional and almost arbitrary observation noise. Numerical simulation of the estimates stabilization for the multidimensional optimization with unknown but bounded deterministic noise is provided. Stabilization bound has sufficiently small level comparing to significant level of noise.

AB - In this paper application of the stochastic approximation algorithm with randomized differences to the minimum tracking problem for the non-constrained optimization is considered. The upper bound of mean-squared estimation error is derived in the case of once differentiable functional and almost arbitrary observation noise. Numerical simulation of the estimates stabilization for the multidimensional optimization with unknown but bounded deterministic noise is provided. Stabilization bound has sufficiently small level comparing to significant level of noise.

KW - NOISE

U2 - 10.1109/CDC.2009.5400839

DO - 10.1109/CDC.2009.5400839

M3 - статья в сборнике материалов конференции

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 5763

EP - 5767

BT - PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009)

PB - IEEE Canada

Y2 - 15 December 2009 through 18 December 2009

ER -

ID: 74014650