Course code 
02 36 6270 00 
Number of ECTS points 
4 
Course title in the language of instruction 
Mathematics for Advanced Signal Processing 
Course title in Polish 
Mathematics for Advanced Signal Processing 
Course title in English 
Mathematics for Advanced Signal Processing 
Language of instruction 
English 
Form of classes 

Lecture 
Tutorials 
Laboratory 
Project 
Seminar 
Other 
Total of teaching hours during semester 
Contact hours 
30 

30 


0 
60 
Elearning 
No 
No 
No 
No 
No 
No 

Assessment criteria (weightage) 
0.50 

0.50 


0.00 


Unit running the course 
Instytut Elektroniki 
Course coordinator 
dr hab. inż. Sławomir Hausman 
Course instructors 
dr hab. inż. Sławomir Hausman, dr inż. Piotr Korbel, prof. dr hab. inż. Paweł Strumiłło 
Prerequisites 
Systems of linear equations, Matrices, Matrix calculus. 
Course learning outcomes 
 Describe linear systems with the use of the underlying mathematics, including representation of signal/vector spaces and approximation theory in vector spaces;
 Implement basic adaptive filter algorithms;
 Apply orthogonal decomposition using harmonic signals and wavelets.

Programme learning outcomes 
 Indepth knowledge and comprehension of complex concepts and phenomena in the field of electronics and telecommunications, methods and theories explaining the dependences between them, as well as main development trends in electronics and telecommunications; knowledge of the fundamentals of life cycle of electronic and telecommunication devices and systems.
 Ability to apply the knowledge to identify, formulate and solve nontypical problems related to electronics and telecommunications, to plan and to conduct adequate experiments, including measurements and numerical simulations also with the aid of selfdeveloped methods and tools, to analyse and to interpret obtained results so as to draw conclusions.

Programme content 
Linear algebra, Hilbert spaces, approximation problem in Hilbert space, linear recursive estimation, least squares method, minimalmean square method, WienerHopf equation, matrix matrix factorization, adaptive filters, timefrequency analysis of signals, wavelets and their application to signal compression. 
Assessment methods 
EK1  written test.
EK2  written test, discussion, laboratory report.
EK3  written test, discussion, laboratory report.

Grading policies 
Lecture  written test.
Laboratory  evaluation of laboratory reports.
Final grade: average of examination grade and laboratory work assesment. 
Course content 
LECTURE
Linear algebra, Hilbert spaces, Approximation problem in a Hilbert space, Least squares filtering, Minimum mean square filtering, WienerHopf equation, Matrix factorization, Adaptive linear filters, Modern spectral estimation, Wavelets and their application to signal compression
LABORATORY
Implementation of selected problems for PC and signal processors 
Basic reference materials 
 Tomasz P. Zieliński, "Cyfrowe przetwarzanie sygnałów", WKŁ, Warszawa, 2005.

Other reference materials 
 Papers available on the internet (artykuły dostępne w sieci Internet)

Average student workload outside classroom 
56 
Comments 

Updated on 
20190726 20:02:23 
Archival course yes/no 
no 