A novel damage indicator from a multivariate linear system model

2016 ◽  
pp. 705-712
Author(s):  
Y. Goi ◽  
C.W. Kim
Keyword(s):  
Linear System ◽  
System Model ◽  
Damage Indicator

SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID

2016 ◽  
Vol 43 (6Part9) ◽  
pp. 3415-3415
Author(s):  
Y Hu ◽  
R Fueglistaller ◽  
J Rottmann ◽  
M Myronakis ◽  
A Wang ◽  
...  
Keyword(s):  
Linear System ◽  
Experimental Validation ◽  
System Model

scholarly journals Experimental validation of a three-dimensional linear system model for breast tomosynthesis

2008 ◽  
Vol 36 (1) ◽  
pp. 240-251 ◽  
Author(s):  
Bo Zhao ◽  
Jun Zhou ◽  
Yue-Houng Hu ◽  
Thomas Mertelmeier ◽  
Jasmina Ludwig ◽  
...  
Keyword(s):  
Linear System ◽  
Experimental Validation ◽  
Three Dimensional ◽  
System Model ◽  
Breast Tomosynthesis

SU-E-I-11: Cascaded Linear System Model for Columnar CsI Flat Panel Imagers with Depth Dependent Gain and Blur

2014 ◽  
Vol 41 (6Part4) ◽  
pp. 132-132 ◽  
Author(s):  
B Peng ◽  
A Lubinsky ◽  
A Teymurazyan ◽  
H Zheng ◽  
W Zhao
Keyword(s):  
Linear System ◽  
System Model ◽  
Flat Panel ◽  
I 11 ◽  
Flat Panel Imagers

The Framework Base on Bayesian Predictive Filtering Algorithm in VR/AR

2014 ◽  
Vol 568-570 ◽  
pp. 1122-1125
Author(s):  
Jian Zhang ◽  
Wan Juan Song
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
Linear System ◽  
Tracking System ◽  
System Model ◽  
Simple Motion ◽  
Filtering Algorithm ◽  
Non Linear ◽  
Non Linear System ◽  
Predictive Filtering

Tracking system is a vital aspect of Virtual Reality and Augmented Reality, the efficiency of tracking system is determined by the implementation of framework and the predictive filtering algorithm. As a result of the better applicability of Bayesian predictive filtering algorithm in simulation of non-linear system model, this paper proposes a framework for Bayesian predictive filter, which includes predictive filtering layer and denotation layer, and according to every layer’s function, analyses the implementation of framework. The optimal simulation count is worked out by the experiment. The results show that in the simulation of non-linear system model, this framework for Bayesian predictive filter can implement the tracking of simple motion and the orientation prediction.

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