IN9340 – Statistical Signal Processing
Course description
Course content
The course covers methods for analysis of digital signals in noise. Examples of topics are description of stochastic signals in time and frequency domain, modeling of signals, estimation, detection, spectral estimation, adaptive filters, and audio signal processing.
Learning outcome
After finishing this course:
- You have very good knowledge about digital signal processing applied on signals in noise.
- You can develop methods to detect signals and estimate parameters from random sequences and frequency spectra.
- You can implement and apply classical and adaptive filters.
- You can develop signal models suitable for modeling random sequences.
- You can implement methods and algorithms in matlab that solve practical problems in statistical signalprocessing.
- You have very good knowledge in signal processing suitable for different applications such as physics,measurement techniques, sensor technology, digital communication, and imaging.
The PhD variant has an extended curriculum within the research area with an additional topic compared to the master variant of the course.
Admission to the course
PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb. If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included.
PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.
Recommended previous knowledge
IN3190 – Digital Signal Processing, MAT1120 – Linear Algebra and IN1000 – Introduction to Object-oriented Programming/IN1900 – Introduction to Programming with Scientific Applications
Overlapping courses
- 10 credits overlap with IN5340 – Statistical Signal Processing.
- 10 credits overlap with INF4480 – Digital Signal Processing II (continued).
- 10 credits overlap with INF9480.
Teaching
4 hours of lectures every other week and 4 hours of group work the opposite weeks.
Submission of mandatory assignments is required. The course consist of 7 topics, each of which will have a mandatory assignment. These assignments will be more advanced than those given in the master variant of the course. Read more about requirements for submission of assignments, group work and legal cooperation under guidelines for mandatory assignments.
Examination
Final written or oral exam which counts 100% of the grade.
The form of the exam will be announced at the beginning of the semester and will depend on the number of participating students.
At least 6 of the 7 mandatory assignments must be approved before you can take the exam, and these assignments must be approved in the same semester.
It will also be counted as one of your three attempts to sit the exam for this course, if you sit the exam for one of the following courses: IN5340 – Statistical Signal Processing, INF4480 – Digital Signal Processing II (continued), INF9480
Language of examination
You may write your examination paper in Norwegian, Swedish, Danish or English.
Grading scale
Grades are awarded on a pass/fail scale. Read more about the grading system.
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.
Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.
More about examinations at UiO
- Use of sources and citations
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.