摘要
本文提出一种新的分区模型结构并给出辨识算法.与此同类型的其它模型结构相比,该模型算法简洁,占用内存少,鲁棒性好,并具有与输入分量尺度无关性和很好的收敛性.
In this paper,a kind of partition model structure and its identification algorithm is presented.Compared with other structures of this group,this model has many good qualities such as simple algorithm,small consuming memory, good robustness and convergence. Furthermore, the identifiearion result is irrelavent to the scales of each input variables.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
1998年第2期304-307,共4页
Control Theory & Applications
关键词
分区模型
格状分区
递推分区
系统辨识
partition model
grid partition
iterative partition
imbalanced training sets