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Proceedings Paper

Systematic construction of order-recursive LS estimation algorithms with elementary orthogonal transformations
Author(s): Fuyun Ling
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Paper Abstract

This paper demonstrates that order-recursive least squares (ORLS) algorithms based on orthogonal transformations and hyperbolic transformations can be systematically constructed in two steps. The first step is to determine the structure of the ORLS algorithm according to the property of the data vector in the LS estimation and the requirements to the output. The second step is to determine the proper implementation of building blocks of the ORLS structure using orthogonal or hyperbolic transformations. The canonical ORLS structure and some possible orthogonal/hyperbolic implementations of their building blocks are presented. It is also shown that some of the orthogonal transformations are only applicable to certain types of ORLS structures and not to others.

Paper Details

Date Published: 1 November 1993
PDF: 12 pages
Proc. SPIE 2027, Advanced Signal Processing Algorithms, Architectures, and Implementations IV, (1 November 1993); doi: 10.1117/12.160448
Show Author Affiliations
Fuyun Ling, Motorola (United States)


Published in SPIE Proceedings Vol. 2027:
Advanced Signal Processing Algorithms, Architectures, and Implementations IV
Franklin T. Luk, Editor(s)

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