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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ELK 518ADAPTIVE SIGNAL PROCESSING - I3 + 02nd Semester7,5

COURSE DESCRIPTION
Course Level Doctorate Degree
Course Type Elective
Course Objective To provide graduate students with the theoretical basis of adaptive signal processing, and to gain students the ability to apply adaptive filtering techniques to real-world problems (e.g. noise cancellation, equalization, interferrence cancellation) in order to improve the performance over static, fixed filtering techniques.
Course Content Adaptive systems / Fundamentals of adaptive filtering / Newton and Steepest-Descent algorithms / The Least Mean-Squares (LMS) algorithm / LMS-based algorithms / The Recursive Least-Squares (RLS) algorithm / RLS-based algorithms / Adaptive IIR filtering / Subband adaptive filtering / Blind adaptive filtering.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1One knows the concepts of adaptive signal processing.
2One knows and applies the Steepest descent algorithm.
3One knows and applies LMS and NLMS based adaptive filters.
4One knows and applies the method of least squares.
5One knows and implements RLS based adaptive filters.
6One can solve noise and echo cancellation problems.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11
LO 001553234 5   
LO 002554255 3   
LO 003554255 3   
LO 004554255 3   
LO 005554255 3   
LO 006553245 5   
Sub Total303022122729 22   
Contribution55425504000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14570
Assignments41040
Report / Project14343
Total Work Load

ECTS Credit of the Course






195

7,5
COURSE DETAILS
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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes