SGN-21006 Advanced Signal Processing, 5 cr

Lisätiedot

Suitable for postgraduate studies.

Vastuuhenkilö

Ioan Tabus

Opetus

Osaamistavoitteet

Student will learn advanced signal processing methods, especially linear optimal filter design, adaptive filters, spectrum estimation, nonlinear filters and how to select proper methods for signal processing tasks at hand. After completing the course, the student - Is familiar with the most important advanced signal processingr generic problems: optimal design, convergence, recursiveness in time, spectrum estimation; - Is able to start from the formulation of a problem formulation and utilize a number of typical algorithmic tools to derive the solution; - Knows what are the most important algorithms for optimal and adaptive filters: LMS, NLMS,RLS etc. - Acquires practice on simulating optimal and adaptive algorithms with given input data and extracting useful performance indices helpful in comparing various algorithms. - Knows how to integrate an optimal or adaptive filter in a number of important applications: echo cancelation, noise cancellation, channel equalization etc.

Sisältö

Ohjeita opiskelijalle osaamisen tasojen saavuttamiseksi

The course is graded on the basis of answers to exam questions. Very good grade is obtained when exam questions are correctly answered and homework is accepted. Course acceptance threshold is approx. half of the maximum exam points. By volunteering to show exercise solutions and solving bonus items in the homework will be rewarded with additional points, to be added to the exam points, and finally the sum will determine the final grade.

Arvosteluasteikko:

Numerical evaluation scale (0-5)

Oppimateriaali

Esitietovaatimukset

Vastaavuudet