Module also offered within study programmes:
General information:
Name:
Frequency Analysis of Signals
Course of study:
2019/2020
Code:
ZSDA-3-0029-s
Faculty of:
Szkoła Doktorska AGH
Study level:
Third-cycle studies
Specialty:
-
Field of study:
Szkoła Doktorska AGH
Semester:
0
Profile of education:
Academic (A)
Lecture language:
English
Form and type of study:
Full-time studies
Course homepage:
 
Responsible teacher:
dr hab. inż. Duda Krzysztof (kduda@agh.edu.pl)
Dyscypliny:
automatyka, elektronika i elektrotechnika, nauki fizyczne
Module summary

Frequency analysis of signals has many applications e.g.: linear system identification, speech processing, image processing, transient analysis, electric power system analysis, radar and sonar systems, communication, nuclear magnetic resonance spectroscopy, mechanical spectroscopy, economics, seismology, weather forecasting, and others. The lecture presents selected methods of frequency analysis: DFT, IpDFT, Prony, Matrix Pencil, and others.

Description of learning outcomes for module
MLO code Student after module completion has the knowledge/ knows how to/is able to Connections with FLO Method of learning outcomes verification (form of completion)
Social competence: is able to
M_K001 Social competences to cooperate in teams working with frequency analysis of signals. SDA3A_K01 Activity during classes
Skills: he can
M_U001 Skill to implement, apply, evaluate, and compare methods for frequency analysis of signals. SDA3A_U01 Activity during classes
M_U002 Skill to self study issues of frequency analysis of signals. SDA3A_U07, SDA3A_U06, SDA3A_U01 Activity during classes
Knowledge: he knows and understands
M_W001 Knowledge of methods for frequency analysis of signals. SDA3A_W02, SDA3A_W01 Activity during classes
Number of hours for each form of classes:
Sum (hours)
Lecture
Audit. classes
Lab. classes
Project classes
Conv. seminar
Seminar classes
Pract. classes
Zaj. terenowe
Zaj. warsztatowe
Prace kontr. przejść.
Lektorat
15 15 0 0 0 0 0 0 0 0 0 0
FLO matrix in relation to forms of classes
MLO code Student after module completion has the knowledge/ knows how to/is able to Form of classes
Lecture
Audit. classes
Lab. classes
Project classes
Conv. seminar
Seminar classes
Pract. classes
Zaj. terenowe
Zaj. warsztatowe
Prace kontr. przejść.
Lektorat
Social competence
M_K001 Social competences to cooperate in teams working with frequency analysis of signals. + - - - - - - - - - -
Skills
M_U001 Skill to implement, apply, evaluate, and compare methods for frequency analysis of signals. + - - - - - - - - - -
M_U002 Skill to self study issues of frequency analysis of signals. + - - - - - - - - - -
Knowledge
M_W001 Knowledge of methods for frequency analysis of signals. + - - - - - - - - - -
Student workload (ECTS credits balance)
Student activity form Student workload
Summary student workload 50 h
Module ECTS credits 2 ECTS
Udział w zajęciach dydaktycznych/praktyka 15 h
Realization of independently performed tasks 35 h
Module content
Lectures (15h):
Subjects:

1. The DFT and Time Windows.
2. The Spectrogram.
3. The Periodogram.
4. The Interpolated DFT.
5. The Cramér-Rao Lower Bound.
7. Parametric frequency estimation.
8. Frequency tracking.

Additional information
Teaching methods and techniques:
  • Lectures: Lecture with the projector and blackboard.
Warunki i sposób zaliczenia poszczególnych form zajęć, w tym zasady zaliczeń poprawkowych, a także warunki dopuszczenia do egzaminu:

The final pass is received based on lecture attendance.
In case of lack of the attendance students are asked to prepare the report on the subject they have missed.

Participation rules in classes:
  • Lectures:
    – Attendance is mandatory: Yes
    – Participation rules in classes: Attendance
Method of calculating the final grade:

The final grade is the pass of lectures.

Sposób i tryb wyrównywania zaległości powstałych wskutek nieobecności studenta na zajęciach:

In case of lack of the attendance students are asked to prepare the report on the subject they have missed.

Prerequisites and additional requirements:

Master degree in electrical engineering.

Recommended literature and teaching resources:

S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Englewood Cliffs, NJ: Prentice-Hall, 1993.

A.V. Oppenheim, R.W. Schafer, J.R. Buck, Discrete-Time Signal Processing, 2nd Edition, Prentice-Hall, 1999.

B. G. Quinn, E. J. Hannan, The Estimation and Tracking of Frequency, New York: Cambridge Univ. Press, 2001.

T.P. Zieliński, Cyfrowe przetwarzanie sygnałów, od teorii do zastosowań, WKŁ, Warszawa, 2005.

K. Duda, Fourierowskie metody estymacji widm prążkowych, Kraków, Wydawnictwa AGH, 2011.

Scientific publications of module course instructors related to the topic of the module:

https://bpp.agh.edu.pl/autor/duda-krzysztof-04141

Additional information:

None