Coursecode: wb2300/5
Coursename: Systems, signals, stochastics

This course is replaced by wb2307

DUT creditpoints: 3
ECTS creditpoints: 5

Faculty of Mechanical Engineering and Marine Technology

Lecturer(s): Stassen, prof.dr.ir. H.G., Dankelman, mw.dr. J.

Tel.: 015-2783607, 5565

Catalog data:
Identification of linear systems in time and frequency domain with deterministic signals. Probability and estimation theory. Description of stochastic processes in time and frequency domain. Identification of linear and non-linear systems with stochastic inputs and outputs. Measurement in open and closed loop systems.

Courseyear: 3
Semester: 0/0/4/0
Hours p/w: 4
Other hours:
Assessment: written
Assessm.period(s): 3, 4
(see academic calendar)

Prerequisites: wb2203, wb2204, wi380

Follow up: wb2301/5, wb2403/5

Detailed description of topics:

  • Reasons and argumentation to introduce stochastic processes in the identification of systems.

  • Identification of (non)linear systems with deterministic input and outputs in frequency and time domain. A recapitulation of system theory, be it now from the viewpoint of the problem of system identification (wb2203 and wb2204).

  • Probability theory. A recapitulation of the mathematics of the probability theory, with a physical interpretation (wi380)

  • Introduction of the estimation theory. Properties of different estimators. The relation between probability domain and time or frequency domain.

  • Stochastic processes. Description of stochastic processes by means of probability density functions. First and second order moments of stochastic processes: mean value, variance, covariance and correlation functions (auto- as well as cross covariance) Spectral density.

  • Identification of linear and non-linear systems with stochastic inputs and outputs. Identification in open and closed loop systems.

  • Many examples and industrial or medical applications will be discussed.

Course material:

A. van Lunteren. Systems, Signals and Stochastic processes. WbMT report w-70. June 1990.

References from literature:

  • A. Papoulis. Probability, Random Variables and Stochastic Processes. McGraw-Hill Book Comp. New York 1995, 583 pp.

  • L. Ljung. System Identification Theory for the user. Prentice-Hall Inc. NJ 1987, 519 pp.

Remarks (specific information about assesment, entry requirements, etc.):

Essential course for all students with interests in system identification.

Goals:

The major goal is to introduce and interprete the theory of the stochastic processes. The actual use of this theory is explained in the courses wb2301 (identification without a-priori knowledge) and wb2403 (parameter estimation)

Computer use:

Laboratory project(s):

Design content:

Percentage of design: n.a.