A modified Prony algorithm for exponential function fitting
SIAM Journal on Scientific Computing
Gram polynomials and the Kummer function
Journal of Approximation Theory
A review of the parameter estimation problem of fitting positive exponential sums to empirical data
Applied Mathematics and Computation
A parameter estimation scheme for damped sinusoidal signals basedon low-rank Hankel approximation
IEEE Transactions on Signal Processing
Nonlinear Approximation by Sums of Exponentials and Translates
SIAM Journal on Scientific Computing
Multi-Sine Fitting Algorithm enhancement for sinusoidal signal characterization
Computer Standards & Interfaces
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In this paper a Prony-like method for non-uniform sampling is proposed. The unknown parameters are estimated on the base of a new linear regression equation which uses filtered signals obtained directly from the measurements. The approach uses the derivative method in the frequency domain yielding exact formula in terms of multiple integrals of the signal, when placed in the time domain. These integrals are explicitly solved by projecting signal on some set of orthogonal basis functions or, more in general, by using a polynomial that fits data in the least-squares sense. The effectiveness of the proposed approach is shown by simulated experiments.