TY - JOUR
T1 - Variable selection in identification of a high dimensional nonlinear non-parametric system
AU - Bai, Er-Wei
AU - Zhao, Wenxiao
AU - Zheng, Weixing
PY - 2015
Y1 - 2015
N2 - The problem of variable selection in system identification of a high dimensional nonlinear non-parametric system is described. The inherent difficulty, the curse of dimensionality, is introduced. Then its connections to various topics and research areas are briefly discussed, including order determination, pattern recognition, data mining, machine learning, statistical regression and manifold embedding. Finally, some results of variable selection in system identification in the recent literature are presented.
AB - The problem of variable selection in system identification of a high dimensional nonlinear non-parametric system is described. The inherent difficulty, the curse of dimensionality, is introduced. Then its connections to various topics and research areas are briefly discussed, including order determination, pattern recognition, data mining, machine learning, statistical regression and manifold embedding. Finally, some results of variable selection in system identification in the recent literature are presented.
KW - dimensionality
KW - linear systems
KW - system identification
KW - variables
UR - http://handle.uws.edu.au:8081/1959.7/uws:30624
U2 - 10.1007/s11768-015-5010-9
DO - 10.1007/s11768-015-5010-9
M3 - Article
SN - 2095-6983
VL - 13
JO - Control Theory and Technology
JF - Control Theory and Technology
IS - 1
ER -
