FYS-2007 | UiT

Type of course

The course is available as a singular course. The course is also available to exchange students and Fulbright students.

Admission requirements

Admission requirements are generell studiekompetanse + REALFA.Local admission, application code 9336 - enkeltemner i realfag.

Course overlap

If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:

FYS-261 Statistics signal theory 9 stp
STA-2003 Time series 8 stp

Course content

The course covers probability theory, random variables and vectors and their probability density functions. Transformations of random variables are discussed, including principal component analysis (whitening). Random time signals are treated in detail, and their characterization in terms of statistical stationarity, correlation functions and power spectral densities, using Fourier transforms, is analyzed. Several different approaches for estimation of correlation functions and power spectral densities based on measurements are developed, and applications e.g. to radar (distance to object) are discussed. Exercises and problem solving, in addition to practical statistical signal processing using programming, are strongly emphasized. Basic programming skills are advantageous.

Recommended prerequisites

FYS-2006 Signal processing, MAT-1003 Calculus 3, MAT-1004 Linear algebra, STA-1001 Probability and statistics

Objectives of the course

Knowledge - The student can:

understand probability theory and the characterization of random variables
describe the concept of a stochastic process and relate it to noise in measured signals
characterize stochastic processes in terms of stationarity, correlation function and power spectral densitiesidentify relevant estimation procedures

Skills - The student can:

calculate probabilities, also by integration over probability density functions
analyze stochastic time signals (processes) in terms of correlation and power
process discrete-time measurements of a random signals using programming
analyze the outcome of the processing in terms of the estimation tools used

General expertise - The student can:

appreciate the importance of statistical signal theory in society
is able to work with statistical signal processing for data analysis
program scripts and functions in Matlab

Language of instruction and examination

The language of instruction is English and all of the syllabus material is in English. Examination questions will be given in English, but may be answered either in English or a Scandinavian language.

Teaching methods

Lectures: 40 hours Exercises: 40 hours

Assessment

Portfolio assessment of a take-home examination counting about 25 % and a final 4 hour written examination counting about 75 %. All components in the portfolio are assessed as a whole and one combined grade is given. Assessment scale: Letter grades A-F. Postponed examination (sections 17 and 21): Students with valid grounds for absence will be offered a postponed examination. Postponed take-home examination is arranged during the semester if possible, otherwise early in the following semester. Postponed written examination is held early in the following semester. See indicated sections in Regulations for examinations at the UiT The arctic university of Norway for more information. Coursework requirements Access to the final examination requires submission of take-home examination.

spring 2018 FYS-2007 Statistical signal theory - 10 ECTS