COURSE INFORMATION Course Title: DIGITAL SIGNAL PROCESSING

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
ECE 336	B	6	3	0	0	3	6

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Julian Hoxha
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Elective
Classroom and Meeting Time:
Course Description:	Digital signal processing concepts spanning from digital filters, to application of Fourier theory for k-space and Z-space filtering. Classic filters and Bessel, Butterworth, and Chebyshev k-space filters. Applications provided through computer implementation of the concepts.
Course Objectives:	The course aims to provide the basic elements for the analysis and design of digital signal processing systems based on the use of numerical techniques. Basic methodologies and techniques are discussed and some of the most advanced topics are introduced whose use is spread in various sectors.

COURSE OUTLINE

Week	Topics
1	Discrete and Continuous Signals. LTI systems.
2	Differential and difference equation for LTI systems.
3	Introduction to Z-Transform.
4	Inverse Z-Transform; Poles and Zero.
5	Radix-2 Fast Fourier Transform and Cooley-Tukey algorithm.
6	Sampling theorem.
7	Filtering with digital systems.
8	Multirate signal processing.
9	FIR filter design.
10	IIR filter design.
11	Adaptive filtering and Wiener filter.
12	Adaptive direct form FIR filter and RLS algorithm.
13	Yule-Walker method.
14	Filter bank.

Prerequisite(s):	Signals & Systems, Calculus I & II, Fundamental of Probability and Discrete Math.
Textbook:	Digital Signal Processing: Principles, Algorithm and Applications, 4th edition, Proakis and Manolakis.
Other References:	Signals and Systems, 3rd edition, Hwei P. Hsu
Laboratory Work:
Computer Usage:
Others:	No

COURSE LEARNING OUTCOMES

1	Knowledge of linear time-invariant systems characterized by differential and difference equations and their solution with initials conditions.
2	Characterization and analysis of LTI discrete time systems & signals in the time domain.
3	Use of z-transform in the analysis of LTI systems.
4	Analysis of signals and LTI systems in frequency domain.
5	Efficient computation of the DFT using radix-2 fast Fourier transform algorithms.
6	Realization of IIR and FIR systems.
7	Implementation of polyphase filter structures.
8	Introduction to adaptive filters based on LMS and RLS algorithm.
9	Knowledge of linear prediction and optimum linear filters (Wiener filters).
10	Knowledge of filter bank and Levinson-Durbin algorithm for solving linear equations.

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Bachelor in Computer Engineering (3 years) Program
1	Engineering graduates with sufficient theoretical and practical background for a successful profession and with application skills of fundamental scientific knowledge in the engineering practice.	5
2	Engineering graduates with skills and professional background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations	5
3	Engineering graduates with the necessary technical, academic and practical knowledge and application confidence in the design and assessment of machines or mechanical systems or industrial processes with considerations of productivity, feasibility and environmental and social aspects.	5
4	Engineering graduates with the practice of selecting and using appropriate technical and engineering tools in engineering problems, and ability of effective usage of information science technologies.	4
5	Ability of designing and conducting experiments, conduction data acquisition and analysis and making conclusions.	4
6	Ability of identifying the potential resources for information or knowledge regarding a given engineering issue.	4
7	The abilities and performance to participate multi-disciplinary groups together with the effective oral and official communication skills and personal confidence.	3
8	Ability for effective oral and official communication skills in foreign language.	3
9	Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology.	3
10	Engineering graduates with well-structured responsibilities in profession and ethics.	3
11	Engineering graduates who are aware of the importance of safety and healthiness in the project management, workshop environment as well as related legal issues.	2
12	Consciousness for the results and effects of engineering solutions on the society and universe, awareness for the developmental considerations with contemporary problems of humanity.	1

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Homework	2	10
Midterm Exam(s)	1	30
Laboratory	1	10
Final Exam	1	40
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	4	64
Hours for off-the-classroom study (Pre-study, practice)	16	3	48
Mid-terms	1	18	18
Assignments			0
Final examination	1	17	17
Other	1	3	3
Total Work Load:			150
Total Work Load/25(h):			6
ECTS Credit of the Course:			6