PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
ELK 518	ADAPTIVE SIGNAL PROCESSING - I	3 + 0	2nd Semester	7,5

COURSE DESCRIPTION

Course Level	Master's 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

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

COURSE'S CONTRIBUTION TO PROGRAM

Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	5	70
Assignments	1	15	15
Mid-terms	1	25	25
Final examination	1	33	33
Presentation / Seminar Preparation	1	10	10
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

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