Schedule

The course will be given during the periods 2018-10-17 -- 20181212 and 20190201-2019-03-15.

Part I: 2018-10-17 --- 2018-12-12 Basic Lectures
* Wednesdays 13.15-15.00
* Lecture 3: Wednesday October 30, 13:15-15:00, Q36, Malvinas väg 6.
* Lecture 4: Wednesday November 7, 13:15-15:00, V23
* Lecture 5: Wednesday November 14, 13:15-15:00, Q36
* Lecture 6: Wednesday November 21, 13:15-15:00, Q21
* Lecture 7: Wednesday November 28, 13:15-15:00, V21, Teknikringen 72
* CANCELLED: Lecture 8: Wednesday December 5, 13:15-15:00, M23. Brinellvägen 64
* Lecture 8: Wednesday December 12, 13:15-15:00, M31, Brinellvägen 64
Extended Lectures (for FEL3202)
* TBD
Part II: 2019-02-01 -- 2019-03-15 Basic Lectures
* Lecture 9: Wednesday January 30,13:15-15:00
* Lecture 10: Wednesday February 6,13:15-15:00
* Lecture 11: Wednesday February 13,13:15-15:00
* Lecture 12: Wednesday February 20, 13:15-15:00In preparation for Lecture 9, read Chapters 2-5 in Ljung. Important in particular¶


* Chapter 2: Signal spectra (Section 2.3) including transformation of signal spectra and spectral factorization.
* Chapter 3: Prediction (Section 3.2) including Lemma 3.1 and one-step ahead predictors, Observers (Section 3.3) , including a family of predictors.
* Chapter 4: A family of transfer function models (Section 4.2), in particular a general family of model structures. State-space models (Section 4.3), in particular innovations representation. Formalia in Section 4.5. Section 4.4 is omitted. Section 4.6 (identifiability) will be covered in Lecture 9.
* Chapter 5: Read as an overview of general model structures. In particular, relate Ljung's view of a model (Section 5.4) to the pdf-model approach we have taken hitherto in the course (Subsection on "An other view of models").
¶


* Lecture 9: Wednesday January 30,13:15-15:00
* Identifiability (Section 4.6 )
* The prediction error approach (Sections 8.1-8.5, 9.1-9.4)
* The correlation approach (Sections 7.7, 8.6, 9.5)

* Lecture 10: Wednesday February 6,13:15-15:00
* Experiment design (Chapter 14 + lecture notes)
* Model structure selection (Chapter 16)

* Lecture 11: Wednesday February 13,13:15-15:00
* Nonlinear stochastic models (Guest lecture by Fredrik Lindsten Uppsala University)

* Lecture 12: Wednesday February 20, 13:15-15:00
* Computing the estimate (Chapter 10)
* Iterative and multi-step methods, including subspace identification, and multi-step least-squares methods (parts of Chapter 7, Chapter 10, and lecture notes)

* Lecture 13: Wednesday March 6, 13:15-15:00
* Biased estimation
* Errors-in-variables estimation
* Identification of dynamical networks
* Concluding remarks

Extended Lectures (for FEL3202)
* TBD
Project presentations
* TBD
Projects are performed in groups of two. The ¶