Tracking of linear time-variant systems
In this paper we exploit the one-to-one correspondences between the recursive least-squares (RLS) and Kalman variables to formulate extended forms of the RLS algorithm. Two particular forms are considered, one pertaining to a system identification problem and the other to the tracking of a chirped sinusoid in additive noise. For both applications, experiments are presented that demonstrate the tracking optimality of the extended RLS algorithms, compared with the standard RLS and least-mean-squares (LMS) algorithms.
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Haykin, S., Sayed, A. H., Zeidler, J., Yee, P., & Wei, P. (1995). Tracking of linear time-variant systems. Conference Record on the IEEE Military Communications Conference, 1995. MILCOM′95, 2, 602–606. https://doi.org/10.1109/MILCOM.1995.483537
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1995
2
602
606
REVIEWED
OTHER
| Event name | Event place | Event date |
San Diego, CA, USA | November 5-8, 1995 | |