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- W2728749916 abstract "This paper is concerned with a method for estimating a mixed spectrum which is composed of multiple sinusoids and an ARMA noise with continuous spectrum. In order to avoid simultaneous minimization of a prediction error criterion with respect to all unknown model parameters, we give an efficient iterative algorithm for estimating the frequencies of the sinusoids and other parameters separately. By adopting the genetic algorithm to choose initial values of the ARMA parameters in the iterative estimation, we can attain a globally optimal estimates of unknown parameters. For executing the proposed hybrid genetic algorithm, a modification of the Toeplitz approximation method is given to estimate the frequencies in the presence of the MA noise, by using a shifted correlation matrix of the filtered observed data. The effectiveness of the proposed algorithm is validated in numerical simulations using the bench mark test data." @default.
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- W2728749916 date "1996-06-01" @default.
- W2728749916 modified "2023-09-27" @default.
- W2728749916 title "Genetic Algorithm Based Mixed Spectrum Estimation for Discrimination of Sinusoids and ARMA Noise" @default.
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- W2728749916 doi "https://doi.org/10.1016/s1474-6670(17)58346-9" @default.
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