COURSE INFORMATION Course Title: SIGNALS AND SYSTEMS

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
ECE 201	B	3	3	0	2	4	7

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Main Course Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Dr. Carlo Ciulla cciulla@epoka.edu.al , Thursdays 11am - 12pm, 1pm - 3pm; Fridays 10am - 12pm;
Second Course 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:	Compulsory
Study program: (the study for which this course is offered)	Bachelor in Electronics and Digital Communication Engineering (3 years)
Classroom and Meeting Time:	ECE - Mondays 10.45am - 13.30pm; Tuesdays 14.45pm 16.30pm - CEN - Wednesdays 8.45am - 11.30am (Group A); 14.45pm - 17.30pm (Group B);
Code of Ethics:	Code of Ethics of EPOKA University Regulation of EPOKA University "On Student Discipline"
Attendance Requirement:	mandatory
Course Description:	Properties of Signals and Systems, Linear and Time Invariant Systems, Convolution in Continuous and Discrete Time Systems, Fourier Analysis of Continuous and Discrete Time Signals, Laplace Transforms, Inverse Laplace Transform, z-Transform, Inverse z-Transform, Transfer (System) Function, Fourier Transform, Discrete Fourier Transform, Difference Equations, Eigenvalues and Eigen functions, Orthogonal Systems, Modulation Concept, Sampling Theorem.
Course Objectives:	To introduce the mathematical tools for analysing signals and systems in the time and frequency domain and to provide a basis for applying these techniques in control and communications engineering.

BASIC CONCEPTS OF THE COURSE

1	Analyzing Discrete and Continuous Time Systems
2	Impulse Response and Convolution
3	Fourier Transform
4	Laplace Transform
5	Z Transform
6	Sampling and Reconstruction
7	Sampling, Interpolation and Model Function Fitting
8	Programming Studies: Implementation of the Theory
9	Gaussian Filter
10	Analysis of Congruency, and Coherence between Fourier, Laplace & Z transforms

COURSE OUTLINE

Week	Topics
1	Introduction to signals and systems.
2	Discrete- time and continuous-time signals properties.
3	Fourier Transform
4	Laplace Transform
5	Z Transform
6	Impulse Response and Convolution
7	Programming the Fourier Transformation: Direct and Inverse
8	Programming the Laplace Transformation: Direct and Inverse
9	Programming the Z Transformation: Direct and Inverse
10	Test cases
11	Nyquist-Shannon sampling theorem.
12	Sampling, Interpolation and Model Function Fitting
13	Gaussian Filter
14	Review

Prerequisite(s):	Calculus I and 2. Discrete mathematics.
Textbook(s):	Allan V. Oppenheim, S. Wilsky and S.H. Nawab, Signals and Systems, Pearson Education, 2007.
Additional Literature:
Laboratory Work:	Yes
Computer Usage:	Yes
Others:	No

COURSE LEARNING OUTCOMES

1	Knowledge of the classification of signals.
2	Knowledge of frequency analysis for continuous-time signals and discrete time signals.
3	Knowledge of linear time-invariant (LTI) systems, as well as of their representation in the time and frequency domains.
4	Knowledge of the analytic signals and systems representation.
5	Programming the Direct & Inverse Fourier Transformation
6	Programming the Direct & Inverse Laplace Transformation
7	Programming the Direct & Inverse Z Transformation
8	Know the difference between Fourier, Laplace and Z Transforms
9	Analysis of Coherence and Congruency of Fourier, Laplace and Z Transformations
10	Test cases

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

No	Program Competencies	Cont.
Bachelor in Electronics and Digital Communication 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.	4
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	5 Ability of designing and conducting experiments, conduction data acquisition and analysis and making conclusions. 4	5
6	6 Ability of identifying the potential resources for information or knowledge regarding a given engineering issue. 4	5
7	The abilities and performance to participate multi-disciplinary groups together with the effective oral and official communication skills and personal confidence.	5
8	Ability for effective oral and official communication skills in foreign language.	5
9	Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology	4
10	10 Engineering graduates with well-structured responsibilities in profession and ethics. 2	4
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.	4
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.	5

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Homework	1	25
Midterm Exam(s)	1	20
Quiz	1	5
Laboratory	1	5
Lab/Practical Exams(s)	1	5
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	3	48
Hours for off-the-classroom study (Pre-study, practice)	12	3	36
Mid-terms	1	22	22
Assignments			0
Final examination	1	22	22
Other	4	11.75	47
Total Work Load:			175
Total Work Load/25(h):			7
ECTS Credit of the Course:			7

CONCLUDING REMARKS BY THE COURSE LECTURER

This section should be completed after the end of the semester