A variable forgetting factor RLS adaptive filtering algorithm

The recursive least squares algorithm (RLS) is realized in MATLAB. Simulation results show that forgetting factor influences the algorithm convergence and stability, which will significantly affect the performance of adaptive filter. Therefore, a variable forgetting factor RLS algorithm is presented...

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Veröffentlicht in:Proceedings, 2009 3rd IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications : 27-29 October 2009, Beijing, China S. 1127 - 1130
1. Verfasser: Junfeng Wang
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.10.2009
Schlagworte:
Adaptive algorithm
Adaptive filter
Adaptive filters
Channel equalization
Convergence
Educational institutions
Filtering algorithms
Finite impulse response filter
Least squares approximation
Least squares methods
Resonance light scattering
RLS
Stability
Variable forgetting factor
ISBN:1424440769, 9781424440764
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:The recursive least squares algorithm (RLS) is realized in MATLAB. Simulation results show that forgetting factor influences the algorithm convergence and stability, which will significantly affect the performance of adaptive filter. Therefore, a variable forgetting factor RLS algorithm is presented in this paper. Simulation results show that the convergence and stability of the variable forgetting factor RLS algorithm (VRLS) are superior to ordinary RLS algorithm. Finally, the RLS algorithm is applied in channel equalization in low SNR and high SNR.
ISBN:1424440769
9781424440764
DOI:10.1109/MAPE.2009.5355946