Controlling error propagation for the recursive least-squares prediction filter

James R. Bunch; Richard C. LeBorne

doi:10.1117/12.160454

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Abstract

The nonlinear nature of the family of fast RLSL algorithms has hindered the study of the numerical properties from a general framework. As more and more applications for these types of fast filters have been realized, the numeric properties have become an essential part of algorithm and hardware development. Most work in the past has been algorithm specific, drawing from a stochastic or a numerical analysis viewpoint. We discuss the numeric behavior of errors propagating between successive filter stages in time and discuss satisfactory conditions which guarantee a stable solution.

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James R. Bunch and Richard C. LeBorne "Controlling error propagation for the recursive least-squares prediction filter", Proc. SPIE 2027, Advanced Signal Processing Algorithms, Architectures, and Implementations IV, (1 November 1993); doi: 10.1117/12.160454; https://doi.org/10.1117/12.160454

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