Course code 02 13 6248 01
ECTS credits 5
Course name in language of instruction 
Advanced Signal Processing
Course name in Polish Advanced Signal Processing
Course name in English 
Advanced Signal Processing
Language of instruction English
Type of classes
Teaching hours per semester
Lecture Tutorials Laboratory Project Seminar Other E-learn.
Contact hours 15 30 30
Distance learning No No No No No No No
Weighted grades 0.50 0.50 0
Unit running the course Instytut Elektroniki
Course coordinator dr inż. Piotr Korbel
Course instructors dr inż. Łukasz Jopek
Prerequisites 
Systems of linear equations, Matrices, Matrix calculus.
Course learning outcomes
  1. EK1 Describe linear systems with the use of the underlying mathematics, including representation of signal/vector spaces and approximation theory in vector spaces
  2. EK2 Implement basic adaptive filter algorithms
  3. EK3 Apply orthogonal decomposition using harmonic signals and wavelets
Assessment methods EK1 - written test. EK2 - written test, discussion, laboratory report. EK3 - written test, discussion, laboratory report.
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.
  3. Ability to communicate effectively with a diverse range of audiences using specialised terminology from electronics and telecommunications also with the aid of English language at B2+ level according to Common European Framework of Reference for Languages; ability to present and to evaluate different opinions and attitudes and to lead and take part in a debate.
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/or digital 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)
Course workload
Type of classes Teaching hours
Lecture 15
Laboratory 30
Other 30
Student`s own work 50
SUM : 125
Comments 

                    

                    

                        Updated on 
                        2022-08-03 13:49:29