Semester 5


Course: Digital Signal Processing



Course Code: ΜΚ28
Course Level: Undergratuate
Obligatory/Elective: Obligatory
Semester: 5
Division: Main Course
Group: Main Course
ECTS Credits: 5
Hours Per Week: 4
Website: eclass.uowm.gr/courses/ICTE113/
Language: Greek
Content:
Course title Digital Signal Processing
Course code ΜΚ28
Course type Compulsory
Course level Undergraduate (first cycle)
Year of studies 3nd
Semester 5th
ECTS Credits 5
URL eclass.uowm.gr/courses/ICTE113/
Hours per week 4
Instructor(s) Markos Tsipouras
Course content Sampling Signal, Oversampling, Subsampling, Frequency Folding, Convolution, Correlation, Discrete Fourier Transform, Z Transform, FIR Digital Filter Design, IIR Digital Filter Design. Applications using MatLab.
Expected learning outcomes and competences to be acquired Upon successful completion of this course, students will be able:
  • to understand simple and complex digital signal processing concepts
  • to perform signal sampling, oversampling and subsampling
  • to calculate signals convolution and correlation
  • to apply DFT and ZT in real or complex signals
  • to design FIR and IIR digital filters
  • to develop software for all the above in MatLa
Prerequisites None
Teaching methods Lectures, theoretical exercises, examples in MatLab, exercises in MatLab
Assessment methods One optional exercise with oral examination (40%)
Final written examination (60%)
Language of instruction Greek
Recommended bibliography
  • [1] ΨΗΦΙΑΚΗ ΑΝΑΛΥΣΗ ΣΗΜΑΤΟΣ, PROAKIS J., MANOLAKIS D., ΕΚΔΟΣΕΙΣ ΊΩΝ, 2010.
  • [2] ΒΑΣΙΚΕΣ ΤΕΧΝΙΚΕΣ ΨΗΦΙΑΚΗΣ ΕΠΕΞΕΡΓΑΣΙΑΣ ΣΗΜΑΤΩΝ, ΜΟΥΣΤΑΚΙΔΗΣ Γ.Β., ΕΚΔΟΣΕΙΣ Α. ΤΖΙΟΛΑ & ΥΙΟΙ Α.Ε., 2004.
  • [3] ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΣΗΜΑΤΟΣ, HAYES M.H., ΕΚΔΟΣΕΙΣ Α. ΤΖΙΟΛΑ & ΥΙΟΙ Α.Ε., 2000.
  • [4] ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑΣ ΣΗΜΑΤΟΣ, ΦΩΤΟΠΟΥΛΟΣ Σ.Δ., ΕΚΔΟΣΕΙΣ ΟΛΥΜΠΙΑ ΑΝ. ΦΩΤΟΠΟΥΛΟΥ, 2010.
Learning Results:

Upon successful completion of this course, students will be able:

  • to understand simple and complex digital signal processing concepts
  • to perform signal sampling, oversampling and subsampling
  • to calculate signals convolution and correlation
  • to apply DFT and ZT in real or complex signals
  • to design FIR and IIR digital filters
  • to develop software for all the above in MatLab
Pre-requirements:

None

Teaching Methods:

Lectures, theoretical exercises, examples in MatLab, exercises in MatLab

Validation:

One optional exercise with oral examination (40%)
Final written examination (60%)

Suggested Books:

[1] ΨΗΦΙΑΚΗ ΑΝΑΛΥΣΗ ΣΗΜΑΤΟΣ, PROAKIS J., MANOLAKIS D., ΕΚΔΟΣΕΙΣ ΊΩΝ, 2010.

[2] ΒΑΣΙΚΕΣ ΤΕΧΝΙΚΕΣ ΨΗΦΙΑΚΗΣ ΕΠΕΞΕΡΓΑΣΙΑΣ ΣΗΜΑΤΩΝ, ΜΟΥΣΤΑΚΙΔΗΣ Γ.Β., ΕΚΔΟΣΕΙΣ Α. ΤΖΙΟΛΑ & ΥΙΟΙ Α.Ε., 2004.

[3] ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΣΗΜΑΤΟΣ, HAYES M.H., ΕΚΔΟΣΕΙΣ Α. ΤΖΙΟΛΑ & ΥΙΟΙ Α.Ε., 2000.

[4] ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑΣ ΣΗΜΑΤΟΣ, ΦΩΤΟΠΟΥΛΟΣ Σ.Δ., ΕΚΔΟΣΕΙΣ ΟΛΥΜΠΙΑ ΑΝ. ΦΩΤΟΠΟΥΛΟΥ, 2010.

Lecturer: Tsipouras Markos