http://www.uu.se/en/admissions/master/selma/kursplan/?kKod=1RT605 1/2

Syllabus for Spectral Processing of SignalsSpektral signalbehandling

5 credits

Course code: 1RT605

Education cycle: Second cycle

Main field(s) of study and in-depth level: Technology A1F

Grading system: Fail (U), 3, 4, 5.

Established: 2011-03-07

Established by: The Faculty Board of Science and Technology

Applies from: week 27, 2011

Entry requirements: 120 credits and Signal processing and Linear algebra.

Responsible department: Department of Information Technology

LEARNING OUTCOMES

The course reviews classical and modern methods and algorithms for computer-based spectral analysis of signals. Also, it gives an overviewof various applications in communications, systems engineering, radar, and biomedicine. After the course, the student will:

understand the spectral estimation problem and the meaning of spectrum

understand the differences between non-parametric and parametric approaches to the spectral estimation problem

master several non-parametric methods for spectral estimation, both periodogram and correlogram-based methods as well as dataadaptive filter-bank methods, and be able to use this knowledge to solve real-world problems

master several parametric methods for estimation of line spectra as well as rational spectra, and be able to use this knowledge tosolve real-world problems

be able to decide what methods ( for example, parametric or non-parametric) are suitable for a specific problem

be able to solve spectral estimation problems and to visualize their solutions using the Matlab software

be prepared to use the tools of spectral analysis of signals for solving practical problems in a diversity of areas such as control systemmodeling, wireless communication systems, radar and sonar signal processing, genomic data mining, image processing, magneticresonance spectroscopy, acoustic imaging, biomedical signal processing, economic, geophysical, astronomic (etc) data processing,internet traffic analysis, and so forth.

CONTENT

Basic definitions and overview of the spectral estimation problem. The periodogram and correlogram methods. Improved methods based onthe periodogram. Filter-bank methods. Parametric methods for rational spectra and for line spectra. Review of selected applications.

5/22/2015 SyllabusforSpectralProcessingofSignalsUppsalaUniversity,Sweden

http://www.uu.se/en/admissions/master/selma/kursplan/?kKod=1RT605 2/2

INSTRUCTIONS

Lectures and computer-based excercises

ASSESSMENT

Graded homework assignments and passed computer excercises.

READING LIST

Applies from: week 27, 2011

Moses Randolph, Stoica PetreSpectral analysis of signalsUpper Saddle River, N.J.: Pearson Prentice Hall, cop. 2005Library catalogueMandatory