Add to ORKGThe objective of this paper is to present an identification procedure which is based on the use of a stochastic linearization method with random coefficients. The model is then defined as a multidimensional linear second-order dynamical system with random coefficients. An optimization procedure is developed to identify the parameters of the probability law of the random coefficients. The identification procedure is described step by step. Finally, an example is presented and shows the interest of the method proposed. 1
A dynamic identification technique in the time domain for time invariant systems under random extern...
A spectral density approach for the identification of linear systems is extended to nonlinear dynami...
A spectral density approach for the identification of linear systems is extended to nonlinear dynami...
It is known that an efficient approach for modal identification of a weakly nonlinear multidimension...
Stochastic approximation methods for the identification of parameters of nonlinear systems without d...
A real time computational method is presented for the identification of linear discrete dynamic syst...
In the article a linear model of n-th order dynamical systems described by the state equation with v...
The industrial demand on good dynamical simulation models is increasing. Since most structures show ...
The industrial demand on good dynamical simulation models is increasing. Since most structures show ...
The problem of nonlinear dynamical systems of Wiener type identification is considered. The linear...
The problem of nonlinear dynamical systems of Wiener type identification is considered. The linear...
A statistical linearization approach is applied to problems of the stationary random response of non...
The first part of the paper examines the asymptotic properties of linear prediction error method est...
A new identification problem of estimating parameters of linear dynamic systems from random threshol...
International audienceThe paper is devoted to the identification of stochastic loads applied to a no...
A dynamic identification technique in the time domain for time invariant systems under random extern...
A spectral density approach for the identification of linear systems is extended to nonlinear dynami...
A spectral density approach for the identification of linear systems is extended to nonlinear dynami...
It is known that an efficient approach for modal identification of a weakly nonlinear multidimension...
Stochastic approximation methods for the identification of parameters of nonlinear systems without d...
A real time computational method is presented for the identification of linear discrete dynamic syst...
In the article a linear model of n-th order dynamical systems described by the state equation with v...
The industrial demand on good dynamical simulation models is increasing. Since most structures show ...
The industrial demand on good dynamical simulation models is increasing. Since most structures show ...
The problem of nonlinear dynamical systems of Wiener type identification is considered. The linear...
The problem of nonlinear dynamical systems of Wiener type identification is considered. The linear...
A statistical linearization approach is applied to problems of the stationary random response of non...
The first part of the paper examines the asymptotic properties of linear prediction error method est...
A new identification problem of estimating parameters of linear dynamic systems from random threshol...
International audienceThe paper is devoted to the identification of stochastic loads applied to a no...
A dynamic identification technique in the time domain for time invariant systems under random extern...
A spectral density approach for the identification of linear systems is extended to nonlinear dynami...
A spectral density approach for the identification of linear systems is extended to nonlinear dynami...