Improved system identification with Renormalization Group.
This paper proposes an improved system identification method with Renormalization Group. Renormalization Group is applied to a fine data set to obtain a coarse data set. The least squares algorithm is performed on the coarse data set. The theoretical analysis under certain conditions shows that the parameter estimation error could be reduced. The proposed method is illustrated with examples.
Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore. Electronic address: elewqg@nus.edu.sg.
Qing-Guo
QG
Wang
Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore. Electronic address: yuchao@nus.edu.sg.
Chao
C
Yu
Qiming Venture Partners, Shanghai 200121, China. Electronic address: yong.zhang@qimingvc.com.
Yong
Y
Zhang
Least squares estimate; Renormalization Group; System identification