Syllabus Application
EE 312
Discrete-Time Signals and Systems
Faculty
Faculty of Engineering and Natural Sciences
Semester
Spring 2025-2026
Course
EE 312 -
Discrete-Time Signals and Systems
Time/Place
Time
Week Day
Place
Date
12:40-14:30
Mon
FENS-L029
Feb 16-May 22, 2026
08:40-09:30
Wed
FENS-L029
Feb 16-May 22, 2026
Level of course
Undergraduate
Course Credits
SU Credit:3, ECTS:6, Basic:1, Engineering:5
Prerequisites
ENS 211
Corequisites
EE 312R
Course Type
Lecture
Instructor(s) Information
Hüseyin Özkan
- Email: hozkan@sabanciuniv.edu
Course Information
Catalog Course Description
Review of linear discrete-time systems and sampled and discrete-time signals; Fourier analysis, discrete and fast Fourier transforms; interpolation and decimation; design of infinite-impulse response and finite impulse response filters. introduction to real time processing using Digital Signal Processors (DSP) chips.
Course Learning Outcomes:
| 1. | At the end of the course, the student is expected to have the ability to construct mathematical models of real life problems and use appropriate methods/software to implement. |
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| 2. | At the end of the course, the student is expected to have learned sampling, and also expected to have the ability to understand and analyze the effect of sampling in the signal level as well as the system level in both time domain and frequency domain. |
| 3. | At the end of the course, the student is expected to have the ability to understand and analyze the discrete-time signals and systems in both time domain and frequency domain. |
| 4. | At the end of the course, the student is expected to have the ability to understand and analyze the discrete-time signals and systems in frequency domain through Discrete Fourier Transform (as an example of finite length discrete transforms). |
| 5. | At the end of the course, the student is expected to have achieved a deeper understanding and the ability of conducting a deeper analysis of discrete-time signals and systems through z-transform |
| 6. | At the end of the course, the student is expected to have the ability to recognize and analyze FIR and IIR filters, and to have achieved a solid understanding of their advantages and disadvantages. |
| 7. | At the end of the course, the student is expected to have learned the fundamentals of IIR (infinite impulse response) filter design and to use Matlab to design IIR filters. |
| 8. | At the end of the course, the student is expected to have learned the fundamentals of FIR (finite impulse response) filter design and to use Matlab to design FIR filters. |
Course Objective
To provide students fundamentals of signal processing in discrete-time and enable them to develop the background for graduate level studies such as adaptive filtering. To provide students knowledge of algorithm design, implementation and analysis through comprehensive experiments/simulations in MATLAB during laboratory sessions.
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