Parameter estimation of moving average processes using cumulants and nonlinear optimization algorithms
نویسندگان
چکیده
In this paper nonlinear optimization algorithms, namely the Gradient descent and the Gauss-Newton algorithms, are proposed for blind identification of MA models. A relationship between third and fourth order cumulants of the noisy system output and the MA parameters is exploited to build a set of nonlinear equations that is solved by means of the two nonlinear optimization algorithms above cited. Simulation results are presented to compare the performance of the proposed algorithms.
منابع مشابه
Blind Identification of MA Models using Cumulants
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