Separable least squares identification of long memory block structured models: Application to lung tissue viscoelasticity

被引：0
|
作者：
Westwick, David T. [1 ]
Suki, Bela [2 ]
机构：
[1] Schulich Sch Engn, Dept Elect & Comp Engn, Calgary, AB, Canada
[2] Boston Univ, Dept Biomed Engn, Boston, MA 02215 USA
来源：
2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15 | 2006年
关键词：
nonlinear system; power law; optimization; tissue strips; stress relaxation; constant phase model;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
A separable least squares algorithm is developed for the identification of a Wiener model whose dynamic element is a constant phase model that has been modified to include a purely viscous term. The separation of variables reduces the dimensionality of the search space from 5 to 2, greatly simplifying the optimization procedure used to estimate the parameters. The algorithm is tested on experimental stress/strain data from a strip of lung parenchyma.
引用
收藏
页码：4466 / +
页数：2
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