Systems Identification. 3 credits

Catalog description

Foundations of parameter estimation using the least squares method. Identification of static and discrete dynamic system models. Batch and recursive (online) approaches. Model order estimation. Persistent excitation requirements. The effect of noise on model accuracy. Nonlinear estimation methods: generalized least squares and maximum likelihood. Applications in control, diagnostics, and economy. Offered by Electrical & Comp. Engineering . May not be repeated for credit.