In this paper we approximate arbitrary complex signals by modeling both the logarithm of the amplitude and the phase of the complex signal as finite-order polynomials in time. We refer to a signal of this type as an exponential polynomial signal (EPS). We propose an algorithm to estimate any desired coefficient for this signal model. We also show how the mean-squared error of the estimate can be determined by using a first-order perturbation analysis. A Monte Carlo simulation is used to verify the validity of the perturbation analysis. The performance of the algorithm is illustrated by comparing the mean-squared error of the estimate to the Cramer-Rao bound for a particular example.
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