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Improvement Of Prony's Method Of System Identification Via Nonlinear Parameter Transformation, C. Wu

Journal of the Arkansas Academy of Science

This paper presents an approach to improve Prony’s method of identifying a linear time-invariant system. The method is based on a nonlinear transformation of parameters, which leads to data averaging. The method yields better results than a direct application of the least squares approach to Prony’s method. A numerical example is given to demonstrate the improvement attained by the new algorithm. Signals are assumed to be contaminated by zero-mean Gaussian white noise.