2013 |
Chetoui, Manel; Malti, Rachid; Thomassin, Magalie; Najar, Slaheddine; Aoun, Mohamed; Abdelkrim, Mohamed Naceur; Oustaloup, Alain Fourth-order cumulants based method for continuous-time EIV fractional model identification Conférence 2013, (Cited by: 4). Résumé | Liens | BibTeX | Étiquettes: Continuous time systems, Continuous-time, Continuous-time system identification, Distributional property, Errors, Errors in variables, Fourth-order cumulants, Fractional differentiation, Fractional model identification, Higher order statistics, Identification (control systems), System identification problems @conference{Chetoui2013c, The errors-in-variables (EIV) system identification problem concerns the dynamic systems whose discrete input and output are corrupted by additive noises, that can be white, colored and/or mutually correlated. In this paper, a new estimator based on Higher-Order Statistics (fourth-order cumulants) is proposed for continuous-time system identification with fractional models. Under some assumptions on the distributional properties of the noise and noise-free signals, the fractional fourth-order cumulants based least squares (ffocls) estimator gives consistent results. A numerical example illustrates the performance of the proposed method. © 2013 IEEE. |
Chetoui, Manel; Malti, Rachid; Thomassin, Magalie; Najar, Slaheddine; Aoun, Mohamed; Abdelkrim, Mohamed Naceur; Oustaloup, Alain Fourth-order cumulants based method for continuous-time EIV fractional model identification Conférence 2013, (Cited by: 4). Résumé | Liens | BibTeX | Étiquettes: Continuous time systems, Continuous-time, Continuous-time system identification, Distributional property, Errors, Errors in variables, Fourth-order cumulants, Fractional differentiation, Fractional model identification, Higher order statistics, Identification (control systems), System identification problems @conference{Chetoui2013, The errors-in-variables (EIV) system identification problem concerns the dynamic systems whose discrete input and output are corrupted by additive noises, that can be white, colored and/or mutually correlated. In this paper, a new estimator based on Higher-Order Statistics (fourth-order cumulants) is proposed for continuous-time system identification with fractional models. Under some assumptions on the distributional properties of the noise and noise-free signals, the fractional fourth-order cumulants based least squares (ffocls) estimator gives consistent results. A numerical example illustrates the performance of the proposed method. © 2013 IEEE. |
Publications
2013 |
Fourth-order cumulants based method for continuous-time EIV fractional model identification Conférence 2013, (Cited by: 4). |
Fourth-order cumulants based method for continuous-time EIV fractional model identification Conférence 2013, (Cited by: 4). |