NDLI: Survey and Evaluation of Automated Model Generation Techniques for High Level Modeling and High Level Fault Modeling

Content Provider	Springer Nature Link
Author	Xia, Likun Farooq, Muhammad Umer Bell, Ian M. Hussin, Fawnizu Azmadi Malik, Aamir Saeed
Copyright Year	2013
Abstract	It is known that automated model generation (AMG) techniques for linear systems are sufficiently mature to handle linear systems during high level modeling (HLM). Other AMG techniques have been developed for various levels of nonlinear behavior and to focus on specific issues such as high level fault modeling (HLFM). However, no single nonlinear AMG technique exists which can be confidently adapted for any nonlinear system. In this paper, a survey on AMG techniques over the last two decades is conducted. The techniques are classified into two main areas: system identification (SI) based AMG and model order reduction (MOR) based AMG. Overall, the survey reveals that more advanced research for AMG techniques is required to handle strongly nonlinear systems during HLFM.
Starting Page	861
Ending Page	877
Page Count	17
File Format	PDF
ISSN	09238174
Journal	Journal of Electronic Testing
Volume Number	29
Issue Number	6
e-ISSN	15730727
Language	English
Publisher	Springer US
Publisher Date	2013-08-24
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Automated model generation High level modeling High level fault modeling Model order reduction and system identification Circuits and Systems Electrical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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