Multi-model approach for nonlinear system identification by EM algorithm
Access Status
Fulltext not available
Authors
Wei, J.
Yin, YanYan
Liu, F.
Date
2017Type
Journal Article
Metadata
Show full item recordCitation
Wei, J. and Yin, Y. and Liu, F. 2017. Multi-model approach for nonlinear system identification by EM algorithm. ICIC Express Letters. 11 (9): pp. 1461-1467.
Source Title
ICIC Express Letters
ISSN
School
Department of Mathematics and Statistics
Collection
Abstract
The problem of system identification for nonlinear system is studied in this paper by using EM algorithm, and a stochastic scheduling parameter which follows a Markov jump process is considered. First, multi-model approach is addressed to describe the nonlinear process, where each linear parameter system is represented by an auto regressive exogenous model, and then, EM algorithm is used to do estimation with the help of stochastic scheduling parameter. A simulation example is given to illustrate the effectiveness of the approach proposed.
Related items
Showing items related by title, author, creator and subject.
-
Besa, Bunda (2010)The decline is a major excavation in metalliferous mining since it provides the main means of access to the underground and serves as a haulage route for underground trucks. However, conventional mining of the decline to ...
-
Lim, Pei Yi (2011)At present, there are still a large number of people living in isolated areas, particularly in developing countries, who have no immediate access to the main electricity grid. Most of the energy demands of these remote ...
-
Zhao, Yu (2006)The design, construction and testing of a reverse-osmosis (PV-RO) desalination system for fresh water shortage area is presented. The system operates from salt water or brackish water and can be embedded in a renewable ...