doi: 10.7763/IJMO.2012.V2.172
Identification of Nonlinear Systems in Presence of Outliers Using Robust Norm and Differential Evolution
Babita Majhi
1
,
H. Pal Thethi
2
,
Jeetamitra Satpathy
3
- 1 Dept. of CS & IT, G. G. Vishwavidyalaya, Central University, Bilaspur, India.
- 2 School of Electronics, KIITS University, Bhubaneswar, India.
- 3 Dept. of Electronics Engg, at Govt. Polytechnic, Bhubaneswar, India.
Abstract
Conventional error based cost function provides unsatisfactory weight update of an adaptive system when outliers are present in the training signal. To alleviate this problem in this paper a hybrid approach using differential evolution (DE) and Wilcoxon norm is proposed to provide robust training in identification of complex nonlinear systems. Exhaustive simulation study shows superior performance of the new method compared to the conventional square error based minimization method.
Keywords
- Differential evolution
- robust system identification
- wilcoxon norm
How to Cite
Babita Majhi, H. Pal Thethi, and Jeetamitra Satpathy, "Identification of Nonlinear Systems in Presence of Outliers Using Robust Norm and Differential Evolution," International Journal of Modeling and Optimization, vol. 2, no. 4, pp. 508-512, 2012. https://doi.org/ 10.7763/IJMO.2012.V2.172
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).