389.170 Signal Processing 2
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2021W, VU, 3.0h, 4.5EC
Lecture TubeTUWEL

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise
  • LectureTube course
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to apply fundamental concepts in the area of probability theory, random variables, and stochastic processes to solve practical engineering problems.

Subject of course

1. One random variable: Cumulative distribution function (cdf) and probability density function (pdf), discrete random variables, transformation of random variables, conditional cdf and pdf, moments, characteristic function, inequalities, conditional expectation, special distributions

2. Two random variables: Joint cdf and pdf, discrete random variables, transformation of random variables, conditional cdf and pdf, moments, correlation, covariance, statistical independence, orthogonality and uncorrelatedness, characteristic function, conditional expectation, special distributions, complex random variables, circular symmetry

3. Random vectors: cdf and pdf, discrete random vectors, transformation of random vectors, conditional cdf and pdf, mean, correlation matrix, covariance matrix, statistical independence, orthogonality and uncorrelatedness, characteristic function, conditional expectation, special distributions, complex random vectors, Karhunen-Loeve decomposition, whitening transformation, innovations representation, MMSE estimation, LMMSE estimation (Wiener filter), ML estimation

4. Random signals (stochastic processes): pdf, stationarity, second-order description (mean, autocorrelation function), cyclostationarity, power spectral density, cross-correlation function und cross-power spectral density, effects of linear systems, time averages und ergodicity, discrete-time random signals, special random signals, complex random signals and circular symmetry, whitening filter, innovations filter, Wold decomposition, AR, MA and ARMA processes, LMMSE estimation (Wiener filter), linear prediction

Teaching methods

Theory lectures on the blackboard, discussion of real-world applications, numerical demonstrations, problem-solving exercises.

Recording of last year's online lectures are available on TUpeerTube: https://tube1.it.tuwien.ac.at/c/sp2

Mode of examination

Written and oral

Additional information

Course starts on Oct. 1, 2021 in lecture hall EI4 - don't miss!

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Fri10:30 - 12:0001.10.2021 - 28.01.2022EI 4 Reithoffer HS - ETIT Vorlesung
Thu11:00 - 12:0007.10.2021 - 27.01.2022EI 4 Reithoffer HS - ETIT Übung
Signal Processing 2 - Single appointments
DayDateTimeLocationDescription
Fri01.10.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu07.10.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri08.10.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu14.10.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri15.10.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu21.10.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri22.10.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu28.10.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri29.10.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu04.11.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri05.11.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu11.11.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri12.11.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu18.11.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri19.11.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu25.11.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri26.11.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu02.12.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung
Fri03.12.202110:30 - 12:00EI 4 Reithoffer HS - ETIT Vorlesung
Thu09.12.202111:00 - 12:00EI 4 Reithoffer HS - ETIT Übung

Examination modalities

- active participation in exercises (solution of problems)

- three-hour written exam (4 problems)

- oral exam

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Mon15:00 - 18:0024.01.2022 Onlinewritten03.01.2022 00:00 - 17.01.2022 00:00TISSSchriftl. Prüfung - Online

Course registration

Begin End Deregistration end
04.10.2021 09:00 19.10.2021 23:59 19.10.2021 23:59

Registration modalities

Course registration required for exercise classes.

Curricula

Literature

Detailed lecture notes for this course will be made available.

Previous knowledge

basic knowledge of mathematics (particularly probability theory and linear algebra) and of signals and system theory (convolution, Fourier analysis, z transform)

Miscellaneous

Language

English