TY - JOUR
T1 - A filtering based recursive least squares estimation algorithm for pseudo-linear auto-regressive systems
AU - Ding, Sheng
AU - Ding, Rui
AU - Yang, Erfu
PY - 2014/3
Y1 - 2014/3
N2 - This paper uses the filtering technique, transforms a pseudo-linear auto-regressive system into an identification model and presents a new recursive least squares parameter estimation algorithm pseudo-linear auto-regressive systems. The proposed algorithm has a high computational efficiency because the dimensions of its covariance matrices become small compared with the recursive generalized least squares algorithm.
AB - This paper uses the filtering technique, transforms a pseudo-linear auto-regressive system into an identification model and presents a new recursive least squares parameter estimation algorithm pseudo-linear auto-regressive systems. The proposed algorithm has a high computational efficiency because the dimensions of its covariance matrices become small compared with the recursive generalized least squares algorithm.
KW - filtering
KW - identification model
KW - least squares parameter estimation
KW - signal processing
UR - http://www.scopus.com/inward/record.url?scp=84894027382&partnerID=8YFLogxK
UR - http://www.sciencedirect.com/science/journal/00160032
U2 - 10.1016/j.jfranklin.2013.10.018
DO - 10.1016/j.jfranklin.2013.10.018
M3 - Article
AN - SCOPUS:84894027382
VL - 351
SP - 1801
EP - 1809
JO - Journal of the Franklin Institute
JF - Journal of the Franklin Institute
SN - 0016-0032
IS - 3
ER -