System Identification Toolbox ||system identification in MATLAB 2021

System Identification Toolbox
Create linear and nonlinear dynamic system models from measured input-output data
#System_Identification_Toolbox#matlab2021#matlabExtension
refer further to the following website
www.mathworks....
the toolbox provides identification techniques such as maximum likelihood, prediction-error minimization (PEM), and subspace system identification. To represent nonlinear system dynamics, you can estimate Hammerstein-Wiener models and nonlinear ARX models with wavelet network, tree-partition, and sigmoid network nonlinearities. The toolbox performs grey-box system identification for estimating parameters of a user-defined model. You can use the identified model for system response prediction and plant modeling in Simulink. The toolbox also supports time-series data modeling and time-series forecasting.