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MTE 829
System Models and Identification
Introduction to modern methods of linear system identification. Different types of models. Review of classic time and frequency-based approach to empirical, 'black-box' system modelling. Non-parametric identification: impulse and step weights, spectral analysis. Parametric, discrete transfer function models from I/O data using Least Squares. Data-collection procedures, model structure selection, use of auto- and cross-correlation functions for diagnostics and model validation, overview of different estimation algorithms.
Weekly Contact: Lab: 1 hr. Lecture: 3 hrs.
GPA Weight: 1.00
Course Count: 1.00
Billing Units: 1
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