General Information

Elective for: BME4, C4, D4, E4-ss, F4, F4-ss, I4, Pi4-ssr, Pi4-biek,Master students mathematical statistics.
Language of instruction: The course will be given in English

Contents

Basic definitions. Extended studies of AR (auto regressive), MA (moving average) och ARMA-processes. Linespectra and parametric estimation methods. Noise-space based techniques. Non-parametric spectral estimators, data-adaptive techniques and multitaper methods. Non-uniform sampling. Orientation of circular and non-circular processes. Spatial spectral analysis. Non-stationary processes. Spectrogram. Wigner-Ville distribution. Cohen class. Ambiguity spectrum. Multitaper techniques for non-stationary signals. Orientation about bispectrum.

Examination details

LTH:

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Approved assignments and project report as well as participation in all compulsary parts. The final grade is given by a summary of the results on the assignments and the written and oral project report.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Parts
Code: 0116. Name: Computer Exercises.
Credits: 3. Grading scale: UG. Assessment: Project with written and oral report
Code: 0216. Name: Assignments Part 1.
Credits: 1. Grading scale: UG. Assessment: The first home assignment
Code: 0316. Name: Assignments Part 2.
Credits: 3,5. Grading scale: UG. Assessment: The rest of the home assignments

NF:

The examination is done written and orally by home assignments and computer
exercise reports

0703 Laboratory Work, 3,0 hp
Grading scale: Fail, Pass
0704 Assignment part 1, 1,0 hp
Grading scale: Fail, Pass
0705 Assignment part 2, 3,5 hp
Grading scale: Fail, Pass

Admission

LTH:

NF:

For admission to the course knowledge equivalent to the courses MASC04, Stationary
Stochastic processes, 7.5 credits and MASM17, Mathematical Statistics: Time series
analysis, 7.5 credits are required together with English B

Reading list

P. Stoica and R. Moses: Spectral analysis of signals. Prentice-Hall, 2005, ISBN: 0-13-113956-8.
M. Sandsten: Lecture notes, Time-frequency analysis. 2011.

Contact and other information

Director of studies: studierektor@matstat.lu.se