NDLI: Cumulants and Genetic Algorithm for Parameters Estimation of Noncausal Autoregressive Models

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Cumulants and Genetic Algorithm for Parameters Estimation of Noncausal Autoregressive Models

Content Provider	Semantic Scholar
Author	Alshebeili, Saleh A. Alsehaili, Mohammad Alkanhal, Majeed A. S.
Copyright Year	2002
Abstract	The authors introduce a new method for estimating the coefficients of a noncausal autoregressive (AR) model. This method is based on a new formulation that relates the unknown AR parameters to both second- and third-order cumulants. The new formulation facilitates the use of linear and nonlinear least-square estimation techniques, and includes some published works as a special case. The nonlinear least-square estimation techniques presented in this work make use of a genetic algorithm (GA) to minimize a cost function that is defined in terms of the model’s output cumulants. We also introduce a new method for estimating the coefficients of a noncausal AR model using the power spectrum and a one-dimensional (1-D) slice of the bispectrum. To illustrate the effectiveness of the proposed AR modelling approaches, extensive simulation examples are presented.
Starting Page	186
Ending Page	196
Page Count	11
File Format	PDF HTM / HTML
DOI	10.1080/02286203.2002.11442240
Volume Number	22
Alternate Webpage(s)	http://www.researchgate.net/profile/Majeed_Alkanhal3/publication/3825699_Cumulants_and_genetic_algorithm_for_parameters_estimation_of_noncausal_AR_models/links/02e7e53345f272bb2a000000.pdf
Alternate Webpage(s)	http://faculty.ksu.edu.sa/alkanhal/selected%20publications/205-2049.pdf
Alternate Webpage(s)	https://doi.org/10.1080/02286203.2002.11442240
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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