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Multiweight optimization in optimal bounding ellipsoid algorithms
Optimal Bounding Ellipsoid (OBE) algorithms offer an attractive alternative to traditional least-squares methods for identification and filtering problems involving affine-in-parameters signal and system models. The benefits-including low computational efficiency, superior tracking ability, and sele...
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| Published in: | IEEE transactions on signal processing 2006-02, Vol.54 (2), p.679-690 |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
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| cited_by | cdi_FETCH-LOGICAL-c381t-1c40187bafeee7407a2ab32249d7ecc974cd1dc4931b808d551a66d9224d64ab3 |
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| cites | cdi_FETCH-LOGICAL-c381t-1c40187bafeee7407a2ab32249d7ecc974cd1dc4931b808d551a66d9224d64ab3 |
| container_end_page | 690 |
| container_issue | 2 |
| container_start_page | 679 |
| container_title | IEEE transactions on signal processing |
| container_volume | 54 |
| creator | Joachim, D. Deller, J.R. |
| description | Optimal Bounding Ellipsoid (OBE) algorithms offer an attractive alternative to traditional least-squares methods for identification and filtering problems involving affine-in-parameters signal and system models. The benefits-including low computational efficiency, superior tracking ability, and selective updating that permits processor multi-tasking-are enhanced by multiweight (MW) optimization in which the data history is considered in determining update times and optimal weights on the observations. MW optimization for OBE algorithms is introduced, and an example MW-OBE algorithm implementation is developed around the recent quasi-OBE algorithm. Optimality of the solution is discussed, and simulation studies are used to illustrate performance benefits. |
| doi_str_mv | 10.1109/TSP.2005.861893 |
| format | article |
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Optimality of the solution is discussed, and simulation studies are used to illustrate performance benefits.</description><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Computational efficiency</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Ellipsoids</subject><subject>Exact sciences and technology</subject><subject>Filtering</subject><subject>Filtering algorithms</subject><subject>Information, signal and communications theory</subject><subject>Iterative algorithms</subject><subject>Least squares method</subject><subject>Mathematical models</subject><subject>Noise robustness</subject><subject>Optimization</subject><subject>Recursive estimation</subject><subject>Samarium</subject><subject>Set-membership identification</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal processing algorithms</subject><subject>Signal, noise</subject><subject>system identification</subject><subject>Technological innovation</subject><subject>Telecommunications and information theory</subject><subject>Tracking</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LxDAQhosoqKtnD16KoJ66O9MkTXIU8QsUBVfwFtI0XSPdZm1aRH-9WSsIHjxlQp55J_MkyQHCFBHkbP74MM0B2FQUKCTZSHZQUsyA8mIz1sBIxgR_3k52Q3gFQEplsZOc3Q1N796tW7z0qV_1buk-de98m7p2vOsmLf3QVq5dpLZp3Cp4V6W6WfjO9S_LsJds1boJdv_nnCRPlxfz8-vs9v7q5vzsNjNEYJ-hoYCCl7q21nIKXOe6JHlOZcWtMZJTU2FlqCRYChAVY6iLopKRqAoa0UlyOuauOv822NCrpQsm_ki31g9BCVnkSIBgJE_-JXMBlAATETz6A776oWvjFkrmgIwQChGajZDpfAidrdWqi1a6D4Wg1uZVNK_W5tVoPnYc_8TqYHRTd7o1Lvy2cZoz8j3-cORcVPL7zHghY8oXqWGL7A</recordid><startdate>20060201</startdate><enddate>20060201</enddate><creator>Joachim, D.</creator><creator>Deller, J.R.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| identifier | ISSN: 1053-587X |
| ispartof | IEEE transactions on signal processing, 2006-02, Vol.54 (2), p.679-690 |
| issn | 1053-587X 1941-0476 |
| language | eng |
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| source | IEEE Xplore (Online service) |
| subjects | Algorithms Applied sciences Computational efficiency Detection, estimation, filtering, equalization, prediction Ellipsoids Exact sciences and technology Filtering Filtering algorithms Information, signal and communications theory Iterative algorithms Least squares method Mathematical models Noise robustness Optimization Recursive estimation Samarium Set-membership identification Signal and communications theory Signal processing Signal processing algorithms Signal, noise system identification Technological innovation Telecommunications and information theory Tracking |
| title | Multiweight optimization in optimal bounding ellipsoid algorithms |
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