Low Complexity Gauss Newton Variable Forgetting Factor RLS for Time Varying System Estimation 


Vol. 41,  No. 9, pp. 1141-1145, Sep.  2016


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  Abstract

In general, a variable forgetting factor is applied to the RLS algorithm for the time-varying parameter estimation in the non-stationary environments. The introduction of a variable forgetting factor to RLS needs heavy additional calculation complexity. We propose a new Gauss Newton variable forgetting factor RLS algorithm which needs small amount of calculation as well as estimates the better parameters in time-varying nonstationary environment. The algorithm performs as good as the conventional Gauss Newton variable forgetting factor RLS and the required additional calculation complexity reduces from O(N²) to O(N).

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  Cite this article

[IEEE Style]

J. Lim and Y. Pyeon, "Low Complexity Gauss Newton Variable Forgetting Factor RLS for Time Varying System Estimation," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 9, pp. 1141-1145, 2016. DOI: .

[ACM Style]

Jun-Seok Lim and Yong-Guk Pyeon. 2016. Low Complexity Gauss Newton Variable Forgetting Factor RLS for Time Varying System Estimation. The Journal of Korean Institute of Communications and Information Sciences, 41, 9, (2016), 1141-1145. DOI: .

[KICS Style]

Jun-Seok Lim and Yong-Guk Pyeon, "Low Complexity Gauss Newton Variable Forgetting Factor RLS for Time Varying System Estimation," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 9, pp. 1141-1145, 9. 2016.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880