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

In 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

Projects are performed in groups of two. The