Spectral Processing of Signals

For information about the location and time of the lectures and labs, see the schedule.

To provide the student with the knowledge necessary to think in the "frequency domain" and to introduce the state-of-the-art methods and algorithms for computer-aided spectral analysis of signals with applications in communications, signal analysis, radar systems, emitter location, signal recognition, and others. More information is available on this page.

Click to download a popular description of the course in ps or pdf format.

Linear algebra, Fourier analysis, Discrete-time signals and systems.

1. Basic definitions and the spectral estimation problem.
2. Periodogram and correlogram methods.
3. Improved periodogram-based methods.
4. Parametric methods for rational spectra.
5. Parametric methods for line spectra.
6. Filter-bank methods.

• Course syllabus
• Lecture slides
• Textbook webpage
• MATLAB m-files and data

In lecture 7 the instructors will present several applications of spectral processing of signals. Similarly, the students have the possibility to get 25 credit points if they present short talks of approximately 20 minutes about some application of spectral processing of signals, either at their choice or by selecting one from the list below (NB: some of these papers might require you to be on the Uppsala University computer network in order to download them):

1. Use of Spectral Analysis in Defense Against DoS Attacks
2. Spectral Analysis of Calcium Oscillations
3. Application of model-based spectral analysis to wind-profiler radar observations
4. Is Spectral Processing Important for Future WSR-88D Radar?
5. High Resolution Analysis of Impact Sounds and Forces
6. Winds under the Rain Forest Canopy: The Aerodynamic Environment of Gliding Tree Frogs
7. A dynamical analysis of tennis: Concepts and data
8. Frequency Spectrum of the Intracardiac and Body Surface ECG during Ventricular Fibrillation - a Computer Model Study
9. Heart-Rate Variability and Event-Related ECG in Virtual Environments
10. A Spectral Analysis of the Frequency of Supermarket Visits
11. Spectral analysis in ecology
12. Comparison of subspace-based methods with AR parametric methods in epileptic seizure detection
13. Spectral analysis of clock noise: a primer
14. Quantitative measurement of speech sound distortions with the aid of minimum variance spectral estimation method for dentistry use

Homework	Exercise from [1]	Deadline	Instructions + exercise
Periodogram methods	C2.22	Sept. 15, 23:59	HW1.pdf
Rational parametric methods	C3.20	Sept. 23, 23:59	HW2.pdf
Rational parametric methods for line spectra	C3.18	Sep. 30, 23:59	HW3.pdf
Parametric methods for line spectra	C4.14	Oct. 13, 23:59	HW4.pdf

The homeworks are to be solved individually, but you are allowed discuss the findings and results with the other students.
The solutions should be handed in electronically via the student portal as PDF (no scans!), or if you don't have access to the student portal, via email to the homework assistant (see above). The homeworks will be returned via the Spectral proc. signals OUT post box on floor 2 in house 2 (box no. 46).

For some general advice on the presentation etc of the homework assignments, please check this page.

Note that in grading the homework solutions we will put emphasis on your interpretations of the results. Also, note that the deadlines are strict! This means that a homework which is handed in late may receive no points at all.

Code for the labs: CompLabs.zip

Lab	Exercise from [1]	Instruction
Periodogram methods	C2.19, C2.20	Lab instruction
Parametric methods for rational spectra	C3.17	--|--
Parametric methods for line spectra	C4.12	--|--
Filter bank methods	C5.13	--|--

Useful MATLAB m-files corresponding to each chapter in the textbook [1] can be downloaded here, but these are already available in the computer labs.

The computer labs are mandatory. If for some reason you cannot attend a specific session, please contact the person responsible for the lab well in advance, or as soon as possible. Make sure that you come to the labs prepared.

For the locations and times of the computer labs, see the schedule.

IMPORTANT: For access to the PC-labs at the department, an account at UpUnet-S (the university computer network for students) is required. Information about UpUnet-S can be found here.

From the computer labs at the IT-department you can access MATLAB scripts for all the labs (so you don't have to do any programming yourself). Those lab-files can be found in two ways. If you have a G: drive mounted when you log into the system you find the files under G:\Program\Systemteknik\Spektralanalys\. If you don't have G: mounted, you can mount the folder needed yourself using "Map Network Drive" and inputting "\\Atena\Program\Systemteknik\Spektralanalys".

The students are required to pass all four labs. The exam consists of solving the four homework assignments. Each homework assignment gives a maximum of 25 points. The points required for the different grades are as follows.

For Master of Science students:

For PhD students:

During the last lecture, the students may choose to present some applications of spectral analysis. Each presentation will last at most 20 minutes (including discussion) and its topic can be selected by the student or suggested by us. For each presentation a maximum of 25 points can be awarded.

[1] P. Stoica and R. Moses, Spectral Analysis of Signals, Prentice-Hall, NJ, USA, 2005. Errata. The book is available for download here :Book