Zobrazeno 1 - 6
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pro vyhledávání: '"Daebum Choi"'
Publikováno v:
Journal of Systemics, Cybernetics and Informatics, Vol 1, Iss 4, Pp 32-37 (2003)
In order to track a maneuvering target, multiple model (MM) methods have been researched. Almost MM algorithms have been developed based on Markov process. However, Markov based MM method is difficult to design and application-dependent. To solve thi
Externí odkaz:
https://doaj.org/article/ab51ec604fd84ac2b7171ebb222714ba
Smart Day-ahead Pump Scheduling Scheme for Electricity Cost Optimization in a Sewage Treatment Plant
Autor:
Daebum Choi, Seungwook Yoon, Taeho Kim, Donghyo Kang, Euiseok Hwang, Changho Mun, Minseob Sim, Yonghwi Kim
Publikováno v:
ICTC
In this paper, we propose a smart coordination scheme of a pump system in the sewage treatment plant. The task is to find an optimal day-ahead joint schedule of multiple pumps in terms of minimizing the electricity cost, while complying system restri
Publikováno v:
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. :620-625
This paper considers the problem of recursive filtering for linear discrete-time systems with uncertain observation. A new approximate adaptive filter with a parallel structure is herein proposed. It is based on the optimal mean square combination of
Publikováno v:
Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, 2004. ISPACS 2004..
This paper considers the problem of fusion of local filters. We derive an optimal mean square combination of arbitrary number of correlated estimates. In particular, for two sensors this combination represents the well-known Millman and Bar-Shalom-Ca
Publikováno v:
Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing (Cat. No.01TH8563).
Variable structure multiple model (VSMM) is one of the most powerful algorithms for effectively tracking a single maneuvering target. Although VSMM is developed specifically to improve the interactive multiple model (MM) method focused to reducing co
Publikováno v:
Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing (Cat. No.01TH8563); 2001, p142-145, 4p