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Proceedings Paper

State Space Model-Based Parameter Estimation Methods And Some Applicatons
Author(s): Bhaskar D. Rao
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Paper Abstract

This paper reviews state space model-based methods for signal processing applications. A state space frame-work is shown to provide a convenient tool for exposing and exploiting structure inherent in many model based methods. It is also shown that there exist state space methods which are robust to noise in data, and to numerical errors. From a computational point of view, the methods are often less complex than existing competing methods. Futhermore they only involve matrix operations which are suitable for systolic/wavefront implementation.

Paper Details

Date Published: 14 November 1989
PDF: 8 pages
Proc. SPIE 1152, Advanced Algorithms and Architectures for Signal Processing IV, (14 November 1989); doi: 10.1117/12.962282
Show Author Affiliations
Bhaskar D. Rao, University of California (United States)

Published in SPIE Proceedings Vol. 1152:
Advanced Algorithms and Architectures for Signal Processing IV
Franklin T. Luk, Editor(s)

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