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
E-learning 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
  1. Describe linear systems with the use of the underlying mathematics, including representation of signal/vector spaces and approximation theory in vector spaces;
  2. Implement basic adaptive filter algorithms;
  3. Apply orthogonal decomposition using harmonic signals and wavelets.
Programme learning outcomes
  1. In-depth 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.
  2. Ability to apply the knowledge to identify, formulate and solve non-typical problems related to electronics and telecommunications, to plan and to conduct adequate experiments, including measurements and numerical simulations also with the aid of self-developed 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, minimal-mean square method, Wiener-Hopf equation, matrix matrix factorization, adaptive filters, time-frequency 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, Wiener-Hopf 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 
  1. Tomasz P. Zieliński, "Cyfrowe przetwarzanie sygnałów", WKŁ, Warszawa, 2005.
Other reference materials 
  1. Papers available on the internet (artykuły dostępne w sieci Internet)
Average student workload outside classroom 
56
Comments 

                    

                    

                        Updated on 
                        2019-07-26 20:02:23
                    

                    

                        Archival course yes/no
                        no