Time Series Analysis and Process Identification
ChE 762

Methods for modelling the dynamic-stochastic behaviour of a process and its disturbances using data collected from the process. Traditional methods for impulse and frequency response identification. Discrete transfer function and ARIMA time series models. Statistical methods for structure determination, parameter estimation, model validation, design of experiments, and analysis of closed-loop data. Use of models for forecasting, analysis, and control.

This course will be offered in future years - not currently available.
Instructor(s): To be announced
Term offered: -
Course level: 700-level
Course outline: Not available
Restrictions: N/A
Co/pre-requisite(s) that may apply: N/A (but confirm on the official registrar page)
Course website: Avenue website

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