Contents


Statistics Refresher

– Sample Mean and Median
– Sample Variance
– Covariance Matrix

System Identification

– Encounter the Main Actors in System Identification
– Location properties: Unbiasedness and Consistency
– Dispersion Properties: The Covariance Matrix
– Likelihood Function
– Fisher Information and Cramér-Rao Lower Bound
– Matching the Model to the Data: Choice of the Error Signal and Cost Function
– Tuning the Model Complexity
Identification of linear-in-the-parameters models
– Recursive Identification – Illustration on the Sample Mean

Design of Excitation Signals

– Sampling – The Bridge Between Continuous-Time and Discrete-Time Signals
– Reconstruction of a Continuous-Time Signal from a Discrete-Time Sequence
– The FFT – The Gate to the Frequency Domain
– Design of Excitation Signals – User Choices
– Periodic Signals – Practical Use
– Swept Sine

Nonparametric Identification

– Under Construction

Identification of Linear Systems

– Under Construction

Identification in the Presence of Nonlinear Distortions

– Under Construction

Identification of Nonlinear Systems

– Under Construction