TY - GEN
T1 - Blind beamformer for constant modulus signals based on relevance vector machine
AU - Hwang, Kyuho
AU - Choi, Sooyong
PY - 2011
Y1 - 2011
N2 - The blind beamforming method for constant modulus (CM) signals based on relevance vector machine (RVM) is proposed. The proposed beamforming method is obtained by incorporating the constant modulus algorithm (CMA)-like error function into the conventional RVM framework. The RVM framework formulates the parameters of beamfomer by exploiting a probabilistic Bayesian learning procedure with assumption of Gaussian prior for parameters. The simulation results show that the proposed blind beamforming method can restore the desired signals with crowded interference signals.
AB - The blind beamforming method for constant modulus (CM) signals based on relevance vector machine (RVM) is proposed. The proposed beamforming method is obtained by incorporating the constant modulus algorithm (CMA)-like error function into the conventional RVM framework. The RVM framework formulates the parameters of beamfomer by exploiting a probabilistic Bayesian learning procedure with assumption of Gaussian prior for parameters. The simulation results show that the proposed blind beamforming method can restore the desired signals with crowded interference signals.
UR - http://www.scopus.com/inward/record.url?scp=80051644807&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80051644807&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2011.5946743
DO - 10.1109/ICASSP.2011.5946743
M3 - Conference contribution
AN - SCOPUS:80051644807
SN - 9781457705397
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2112
EP - 2115
BT - 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
T2 - 36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Y2 - 22 May 2011 through 27 May 2011
ER -