TY - GEN
T1 - Partial update conjugate gradient algorithms for adaptive filtering
AU - Xie, Bei
AU - Bose, Tamal
PY - 2011
Y1 - 2011
N2 - In practice, computational complexity is an important consideration of an adaptive signal processing system. A well-known approach to controlling computational complexity is applying partial update (PU) adaptive filters. In this paper, a partial update conjugate gradient (CG) algorithm is employed. Theoretical analyses of mean and mean-square performance are presented. The simulation results of different PU CG algorithms are shown. The performance of PU CG algorithms are also compared with PU recursive least squares (RLS) and PU Euclidean direction search (EDS) algorithms.
AB - In practice, computational complexity is an important consideration of an adaptive signal processing system. A well-known approach to controlling computational complexity is applying partial update (PU) adaptive filters. In this paper, a partial update conjugate gradient (CG) algorithm is employed. Theoretical analyses of mean and mean-square performance are presented. The simulation results of different PU CG algorithms are shown. The performance of PU CG algorithms are also compared with PU recursive least squares (RLS) and PU Euclidean direction search (EDS) algorithms.
KW - Conjugate gradient adaptive filter
KW - Partial update
KW - Recursive algorithms
UR - http://www.scopus.com/inward/record.url?scp=80052502975&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80052502975&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:80052502975
SN - 9789898425485
T3 - PECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems
SP - 317
EP - 323
BT - PECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems
T2 - 1st International Conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2011
Y2 - 5 March 2011 through 7 March 2011
ER -