Semester 5


Course: Digital Signal Processing



Course Code: ΜΚ28
Course Level: Undergratuate
Obligatory/Elective: Elective
Semester: 5
Division: Main Course
Group: Main Course
ECTS Credits: 5
Hours Per Week: 4
Website: eclass.uowm.gr/courses/ICTE113/
Language: Greek
Content:

• Introductory Concepts, Continuous and Discrete Signals, Analog to Digital Converting,
Sampling, Nyquist / Shannon Theorem, Quantum, Coding
• Discrete Time Signals, Discrete Time Signal Properties, Independent Variable
Transformations, Dependent Variable Transformations, Signal Characteristics.
• Introduction to Discrete Time Systems, Classification of DT Systems, LTI Systems Analysis
Techniques, Convolution Method, Directs Methods for Solving Difference Equations, The
Convolution Theorem, Properties of Convolution, Convolution Calculating, Difference
equations, Solving Difference Equations with Linear Factors, Classification, Impact Response.
• Introduction to Fourier Analysis, Discrete Time Fourier Transform, Discrete Time Fourier
Transform Properties, Discrete Fourier Series, Discrete Fourier Transform, Discrete Fourier
Transform Properties.
• Fast Fourier Transform, The aim of Fast Fourier Transform, Butterfly network, Frequency
Division and Time division multiplexing, Fast convolution – Overlap – Add and Overlap –
Save Method, Discrete cosine transform.
• Z – Transform, Ζ – Transform properties, Use Z – Transform to solve Difference Equations,
The Z – Transform utility in the analysis of discrete Linear and Time invariant systems,
Inverse Z – Transform, Calculate Inverse Z – Transform.
• The concept of frequency response, Introduction to Transfer Function, Effect of poles on
frequency response, Implementation Discrete Systems.
• Introduction to Filters, Finite Impulse Response Filters (FIR), The concept of linear phase,
Median Filtering, FIR Design, Infinite Impulse Response Filters (IIR), IIR Design, Lowpass
Analog Filters, IIR Filter Design.

Learning Outcomes:

Upon successful completion of this course, students will be able:
• to understand simple and complex concepts of digital signal
processing.
• to perform sampling, oversampling, under sampling.
• to calculate convolution and correlation in signals.
• to apply DFT and ZT to real or complex signals.
• to design FIR and IR digital filters.
• to design software for all of the above in MATLAB.

Pre-requirements:

None

Teaching Methods:
Method Description Semester Workload
  26
  26
  25
  8
  40
Total 125
Validation:

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

Suggested Books:

1. DIGITAL SIGNAL ANALYSIS, PROAKIS J., MANOLAKIS D., ION
PUBLICATIONS, 2010.
2. BASIC TECHNIQUES OF DIGITAL SIGNAL PROCESSING,
MOUSTAKIDIS GV, A. TZIOLA & SONS PUBLICATIONS SA, 2004.
3. DIGITAL SIGNAL PROCESSING, HAYES M.H., A. TZIOLA & SONS
PUBLICATIONS SA, 2000.
4. DIGITAL SIGNAL PROCESSING, FOTOPOULOS SD, OLYMPIA
PUBLICATIONS AN. PHOTOPOULOU, 2010.

Lecturer: Tsipouras Markos