Journal of applied mathematics & informatics
- Volume 22 Issue 1_2
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- Pages.373-385
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- 2006
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- 2734-1194(pISSN)
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- 2234-8417(eISSN)
A PARAMETER ESTIMATION METHOD FOR MODEL ANALYSIS
- Oh Se-Young (Department of Mathematics, Chungnam National University) ;
- Kwon Sun-Joo (Department of Mathematics, Chungnam National University) ;
- Yun Jae-Heon (Department of Mathematics, Institute for Basic Sciences & College of Natural Sciences, Chungbuk National University)
- Published : 2006.09.01
Abstract
To solve a class of nonlinear parameter estimation problems, a method combining the regularized structured nonlinear total least norm (RSNTLN) method and parameter separation scheme is suggested. The method guarantees the convergence of parameters and has an advantages in reducing the residual norm over the use of RSNTLN only. Numerical experiments for two models appeared in signal processing show that the suggested method is more effective in obtaining solution and parameter with minimum residual norm.
Keywords
- Model analysis;
- parameter estimation;
- regularized structured nonlinear total least norm;
- residual norm reduction