First Cycle - Faculty of Engineering - Computer Engineering (English)
Y : Year of Study S : Semester
Course Unit Code Course Unit Title Type of Course Y S ECTS
CSE3048 Introduction to Signals and Systems Compulsory 3 6 5
Objectives of the Course
to introduce students to the basic concepts of signals, system modeling, and system classification; to develop students’ understanding of time-domain and frequencydomain approaches to the analysis of continuous and discrete systems
Learning Outcomes
1 Know how to sample a discrete signal, and how to construct continuous signal back from the discrete signal.
2 know about Fourier series and Fourier transform. Know its relation to convolution.
3 know convolution in both discrete and continuous context. know how convolution is applied to LTI differential / difference equations.
4 know the concepts of linearity, time invariance and casuality.
5 Manipulate complex numbers, Know about dirac delta function
Mode of Delivery
Formal Education
Recommended Optional Programme Components
Course Contents
Discrete-time and continuous time signals, convolution. Fourier series. Fourier and Laplace transforms. Discrete Fourier and Z-transforms. Linear, time-invariant systems: impulse response, system function. Filtering.Sampling theory. Nyquist sampling theorem.
Weekly Detailed Course Contents
Week Theoretical Practice Laboratory
1 Introduction to Complex Numbers Euler's rule
2 Continuous signals sine, cosine, exponential. Unit step Dirac delta.
3 Discrete signals Discrete cımplex exponential. Differences from continuous complex exponential. Discrete unit step. Discrete dirac delta.
4 Discrete systems Example: Difference and differential equations Casuality, Time invariance, linearity. Principle of superposition.
5 Discrete LTI systems representation of signals in terms of impulses. impulse response function and convolution sum An example of a L, but not TI system.
6 Continuous LTI systems Convolution integral
7 LTI systems represented by differential and difference equations.
9 Continuous-time fourier series Convergence Problem.
10 Continuous time fourier transform Continuous time FT of periodic signals
11 Properties of continuous time FT. The convolution property The modulation property Frequency response of LTI ode's.
12 Discrete time fourier series Discrete time fourier transform Periodic signals and Discrete time fourier transformation.
13 Properties of discrete time FT. The convolution property The modulation property Frequency response of LTI difference equations.
14 Filtering. Sampling theory. Nyquist sampling theorem.
15 Laplace and z transformations.
16 Final Exam Study
17 Final Exam
Recommended or Required Reading
Signals and Systems, Oppenheim, Willsky, and Young, Prentice-Hall, 1983, ISBN No: 0-13-809731-3.
Planned Learning Activities and Teaching Methods
Lecture Notes Projects Some computer lab exercises are used to introduce Matlab Programming assignment for speech processing as application of Signal processing
Term (or Year) Learning Activities60
End Of Term (or Year) Learning Activities40
Term (or Year) Learning ActivitiesQuantityWeight
Midterm Exam150
End Of Term (or Year) Learning ActivitiesQuantityWeight
Final Exam1100
Language of Instruction
Work Placement(s)
Workload Calculation
Activities Number Time (hours) Total Work Load (hours)
Theoretical 3 14 42
Pre Class Self Study 1 14 14
Post Class Self Study 2 14 28
Midterm Preparation 1 15 15
Final Preparation 1 15 15
Total 8 72 114
Contribution of Learning Outcomes to Programme Outcomes
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