Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
S. Golden , Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA
B. Friedlander , Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA
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 present a computationally efficient algorithm that estimates the unknown parameters by successively solving a series of optimization problems that are only a function of a single unknown complex parameter. At high signal-to-noise ratios, the mean-squared error of the estimates are shown to be close to the Cramer-Rao bound for a particular example by using a Monte Carlo simulation.<
polynomials, signal representation, computational complexity, parameter estimation, optimisation, Monte Carlo methods, Gaussian noise, white noise
S. Golden and B. Friedlander, "Estimating exponential polynomial signals," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 811-815.