Add to ORKGA prediction error estimation algorithm is derived for the estimation of complex number systems. The algorithm is applied to reconstruct both linear and nonlinear differential equation models from frequency response data. A simulation study is included to illustrate the algorithm
The application of linear prediction to frequency estimation for sinusoidal signals in noise is inve...
We propose a continuous-time prediction error identification method to identify combined determinist...
The paper presents a novel approach to approximation of a linear transfer function model, based on d...
SIGLEAvailable from British Library Document Supply Centre- DSC:7769.0858(SU-DCS-RR--421) / BLDSC - ...
This contribution describes a common family of estimation methods for system identification, viz, pr...
AbstractThis paper investigates the forecasting accuracy of different prediction methods based on th...
A novel Bayesian paradigm to identification of output error models has been recently proposed where,...
This paper treats several aspects relevant to the identification of continuous-time output error (OE...
This paper treats identification of continuous-time output error (OE) models based on sampled data. ...
In this report recursive algorithm for estimation of model error in continuous time system is presen...
This paper analyzes two recent methods for the nonparametric estimation of the Frequency Response Fu...
Parametric identification of linear time-invariant (LTI) systems with output-error (OE) type of nois...
A novel direct approach for identifying continuous-time linear dynamic errors-in-variables models is...
Algorithms are presented for estimation of deterministic model error in the assumed models of nonlin...
Recursive state and parameter reconstruction is a well-established field in control theory. In the c...
The application of linear prediction to frequency estimation for sinusoidal signals in noise is inve...
We propose a continuous-time prediction error identification method to identify combined determinist...
The paper presents a novel approach to approximation of a linear transfer function model, based on d...
SIGLEAvailable from British Library Document Supply Centre- DSC:7769.0858(SU-DCS-RR--421) / BLDSC - ...
This contribution describes a common family of estimation methods for system identification, viz, pr...
AbstractThis paper investigates the forecasting accuracy of different prediction methods based on th...
A novel Bayesian paradigm to identification of output error models has been recently proposed where,...
This paper treats several aspects relevant to the identification of continuous-time output error (OE...
This paper treats identification of continuous-time output error (OE) models based on sampled data. ...
In this report recursive algorithm for estimation of model error in continuous time system is presen...
This paper analyzes two recent methods for the nonparametric estimation of the Frequency Response Fu...
Parametric identification of linear time-invariant (LTI) systems with output-error (OE) type of nois...
A novel direct approach for identifying continuous-time linear dynamic errors-in-variables models is...
Algorithms are presented for estimation of deterministic model error in the assumed models of nonlin...
Recursive state and parameter reconstruction is a well-established field in control theory. In the c...
The application of linear prediction to frequency estimation for sinusoidal signals in noise is inve...
We propose a continuous-time prediction error identification method to identify combined determinist...
The paper presents a novel approach to approximation of a linear transfer function model, based on d...