Title :
Analysis of outliers in system identification using WLMS algorithm
Author :
Dash, Shishir ; Mohanty, Mihir Narayan
Author_Institution :
Electron. & Commun. Eng. Dept., Siksha `O´ Anusandhan Univ., Bhubaneswar, India
Abstract :
Outliers play an important role in adaptive systems. The rank-based Wilcoxon approach to linear regression problems in statistics are usually insensitive to outliers. This paper aim towards the Wilcoxon approach in Least Mean Square Algorithm. Also it has been applied for System Identification problem with Gaussian noise. The traditional LMS algorithm is generally well suited for identification of linear static systems where the probability of addition of outliers to data input is minimal. The investigation regarding the performance the performance analysis, error curve and deviation in presence of outliers are presented. Simulation results show that the Wilcoxon norm based LMS have better robustness against outliers.
Keywords :
Gaussian noise; data analysis; identification; least mean squares methods; regression analysis; Gaussian noise; WLMS algorithm; adaptive systems; error curve; least mean square algorithm; linear regression problems; linear static system identification problem; outlier analysis; performance analysis; rank-based Wilcoxon approach; Algorithm design and analysis; Heuristic algorithms; Lead; Least squares approximation; Object recognition; Optimization; Robustness; Outliers; System Identification; WLMS algorithm; Wilcoxon norm;
Conference_Titel :
Computing, Electronics and Electrical Technologies (ICCEET), 2012 International Conference on
Conference_Location :
Kumaracoil
Print_ISBN :
978-1-4673-0211-1
DOI :
10.1109/ICCEET.2012.6203842
