An alternative solution to the model structure selection problem is introduced by conducting a forward search through the many possible candidate model terms initially and then performing an exhaustive all subset model selection on the resulting model. An example is included to demonstrate that this approach leads to dynamically valid nonlinear model
Two of the steps in system identification are model structure selection and parameter estimation. In...
System identification is a field of study involving the derivation of a mathematical model to explai...
A new nonlinear rational model identification algorithm is introduced based on genetic algorithms. ...
An alternative solution to the model structure selection problem is introduced by conducting a forwa...
Model structure selection plays a key role in nonlinear system identification. The first step in non...
Model structure selection plays a key role in non-linear system identification. The first step in no...
A new algorithm which preselects variables in nonlinear system models is introduced by converting t...
A new adaptive orthogonal least squares (AOLS) algorithm is proposed for model subset selection and ...
A new adaptive orthogonal search (AOS) algorithm is proposed for model subset selection and non-line...
The identification of polynomial Nonlinear Autoregressive [Moving Average] models with eXogenous var...
In model identification, the existence of uncertainty normally generates negative impact on the accu...
In nonlinear system identification, the available observed data are conventionally partitioned into ...
Model structure selection (MSS) is a critical problem in the nonlinear identification field. In the ...
In non-linear system identification, the available observed data are conventionally partitioned into...
Abstract: In nonlinear system identification, the available observed data are conventionally partiti...
Two of the steps in system identification are model structure selection and parameter estimation. In...
System identification is a field of study involving the derivation of a mathematical model to explai...
A new nonlinear rational model identification algorithm is introduced based on genetic algorithms. ...
An alternative solution to the model structure selection problem is introduced by conducting a forwa...
Model structure selection plays a key role in nonlinear system identification. The first step in non...
Model structure selection plays a key role in non-linear system identification. The first step in no...
A new algorithm which preselects variables in nonlinear system models is introduced by converting t...
A new adaptive orthogonal least squares (AOLS) algorithm is proposed for model subset selection and ...
A new adaptive orthogonal search (AOS) algorithm is proposed for model subset selection and non-line...
The identification of polynomial Nonlinear Autoregressive [Moving Average] models with eXogenous var...
In model identification, the existence of uncertainty normally generates negative impact on the accu...
In nonlinear system identification, the available observed data are conventionally partitioned into ...
Model structure selection (MSS) is a critical problem in the nonlinear identification field. In the ...
In non-linear system identification, the available observed data are conventionally partitioned into...
Abstract: In nonlinear system identification, the available observed data are conventionally partiti...
Two of the steps in system identification are model structure selection and parameter estimation. In...
System identification is a field of study involving the derivation of a mathematical model to explai...
A new nonlinear rational model identification algorithm is introduced based on genetic algorithms. ...