Frequency estimation of undamped exponential signals using genetic algorithms

Authors:
Amit Mitra;Debasis Kundu;Gunjan Agrawal
Affiliations:
Department of Mathematics & Statistics, Indian Institute of Technology Kanpur, Kanpur 208016, India;Department of Mathematics & Statistics, Indian Institute of Technology Kanpur, Kanpur 208016, India;Department of Operations Research and Statistics, University of North Carolina at Chapel Hill, USA
Venue:
Computational Statistics & Data Analysis
Year:
2006

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Abstract

In this paper, we consider the problem of frequency estimation of undamped superimposed exponential signals model. We propose two iterative techniques of frequency estimation using genetic algorithms. The proposed methods use an elitism based generational genetic algorithm for obtaining the least squares and the approximate least squares estimates. In the simulation studies, it is observed that the proposed methods give nearly efficient estimates, having mean square error almost attaining the corresponding Cramer-Rao lower bound. The proposed methods significantly do not depend on the initial guess values otherwise required for other iterative methods of frequency estimation. It is also observed that the proposed methods have fairly high breakdown point with respect to different types of outliers present in the data. Outlier robustness and accuracy of the proposed methods are compared with the classical approaches for this problem.