TY - JOUR
T1 - Improved performance analysis of recursive least squares algorithm
AU - Xiong, Y.
AU - Leung, S. H.
AU - Yin, J. X.
PY - 2001/11
Y1 - 2001/11
N2 - This paper discussed the performance analysis of the recursive least squares (RLS) algorithm. Both mean and mean square behavior are studied. By using novel and more accurate approaching method, accompany with averaging principle, an improved performance analysis of mean square behavior is carried out. It is shown that the theoretical analysis analysis and the simulation result are close to each other, outperforming of the conventional analysis of RLS algorithm. The stability of the basic RLS algorithm is discussed under the new analysis result.
AB - This paper discussed the performance analysis of the recursive least squares (RLS) algorithm. Both mean and mean square behavior are studied. By using novel and more accurate approaching method, accompany with averaging principle, an improved performance analysis of mean square behavior is carried out. It is shown that the theoretical analysis analysis and the simulation result are close to each other, outperforming of the conventional analysis of RLS algorithm. The stability of the basic RLS algorithm is discussed under the new analysis result.
KW - Mean square error analysis
KW - Recursive least mean square error
KW - Stability
UR - http://www.scopus.com/inward/record.url?scp=0035519225&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0035519225&origin=recordpage
M3 - RGC 22 - Publication in policy or professional journal
SN - 1000-565X
VL - 29
SP - 32
EP - 36
JO - Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)
JF - Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)
IS - 11
ER -