TY - GEN
T1 - Using the pearson correlation coefficient to develop an optimally weighted cross relation based blind SIMO identification algorithm
AU - Huang, Yiteng
AU - Benesty, Jacob
AU - Chen, Jingdong
PY - 2009
Y1 - 2009
N2 - Blind SIMO identification is challenging when additive noise is strong and for ill-conditioned/acoustic SIMO systems. A weighted cross relation (CR) algorithm presumably can be robust to noise but there lacks a practical way to define the weights. In this paper, the Pearson correlation coefficient (PCC) is used to develop an optimally weighted CR algorithm, which is validated by simulations.
AB - Blind SIMO identification is challenging when additive noise is strong and for ill-conditioned/acoustic SIMO systems. A weighted cross relation (CR) algorithm presumably can be robust to noise but there lacks a practical way to define the weights. In this paper, the Pearson correlation coefficient (PCC) is used to develop an optimally weighted CR algorithm, which is validated by simulations.
KW - Acoustic SIMO system
KW - Blind identification
KW - Pearson correlation coefficient
KW - Weighted cross relations
UR - http://www.scopus.com/inward/record.url?scp=70349211659&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2009.4960293
DO - 10.1109/ICASSP.2009.4960293
M3 - 会议稿件
AN - SCOPUS:70349211659
SN - 9781424423545
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 3153
EP - 3156
BT - 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
T2 - 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
Y2 - 19 April 2009 through 24 April 2009
ER -