Course Information
Cycle / Level1st / Undergraduate, 2nd / Postgraduate
Teaching PeriodWinter
CoordinatorKonstantinos(constantine) Kotropoulos
Course ID40002942

Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)

Registered students: 170
OrientationAttendance TypeSemesterYearECTS
GENIKĪ KATEUTHYNSĪCompulsory Course537

Class Information
Academic Year2019 – 2020
Class PeriodWinter
Faculty Instructors
Weekly Hours6
Class ID
Course Type 2016-2020
  • Background
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
General Prerequisites
Prior exposition to linear algebra, calculus of functions of one independent real variable, complex analysis, and differential equations can facilitate the faster grasping of the concepts introduced.
Learning Outcomes
Cognitive: Thorough grasp of signals as information bearing carriers. Acquaintance with linear system theory; Unified and comparative treatment of continuous-time and discrete-time signals and systems; Introduce the frequency content of a signal as latent information inherent in its time-domain representation. Treatment of discrete-time signal transforms as algorithms of their continuous-time counterparts. Skills: Promoting analytic skills; Building the necessary theoretical foundation for the transition from system analysis to system design and proceeding to advanced studies in image processing, speech and audio processing, biomedical signal processing. Programming speech processing and audio coding applications in MATLAB.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Signals and systems. Linear time-invariant systems. Fourier transform for continuous-time signals and systems. Sampling. The z-transform. Fourier series representation of discrete-time periodic signals. The discrete-time Fourier transform. The discrete Fourier transform. Programming in MATLAB algorithms for speech processing in cellular phones and audio coding in MP3 players.
Linear Time-Invariant Filters, Fourier Transform, Z-Transform, Discrete Fourier Transform, Filters
Educational Material Types
  • Notes
  • Slide presentations
  • Video lectures
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Slides and MATLAB demos
Course Organization
Laboratory Work75
Student Assessment
a.1 Six lab exercises are offered in the course. The attendance of the lab exercises is compulsory. Students' performance in the lab exercises contributes up to 3 grades in their grading. a.2 A mid-term exam is organized around the 7th semester week. Students' participation in the mid-term exam is optional. Students' papers in the mid-term exam contribute up to 3.5 grades in their grading. a.3 To reward the hard-working students and to motivate lecture attendance, ten-min tests are conducted without prior notice during the semester. The tests aim at assessing if the topics discussed in the class are made clear to the students. No preparation is needed. In addition, optional homework projects are assigned to interested students. Students' performance in the tests and projects contributes up to 2 bonus grades. a.4 The final exams during January and September cover all topics taught. Students' paper rating contributes up to 7 grades in their grading. The papers are divided into two equal parts. The first part covers the topics taught up to the mid-term exam and the second one the remaining topics. Students, who participated in the mid-term exams, may choose to be examined in either the second part of the paper or the full paper. The students are promoted if their final grade is greater than or equal to 5.
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
  • Labortatory Assignment (Formative, Summative)
Course Bibliography (Eudoxus)
Θεοδωρίδης Σ., Μπερμπερίδης Κ., Κοφίδης Λ. «Εισαγωγή στη Θεωρία Σημάτων & Συστημάτων», Εκδόσεις Τυποθήτω-Δαρδανός, Αθήνα, 2003. Oppenheim A.V., Wilsky A. S., Nawab S. H. (μτφ.) «Σήματα και Συστήματα», Εκδόσεις Φουντάς, Αθήνα 2011.
Additional bibliography for study
J. McClellan, R. W. Schafer, and M. A. Yoder, Signal Processing First. Upper Saddle River, N.J.: Pearson Education Prentice Hall, 2003. H. P. Hsu, Signals and Systems. New York, N.Y.: Schaum's Outlines, McGraw-Hill, 1995. C. L. Phillips, J. M. Parr, and E. A. Riskin, Signals, Systems, and Transforms, 4/e. Upper Saddle River, N.J.: Pearson Education, 2008. E. Kudeki and D. C. Munson, Jr., Analog Signals and Systems. Upper Saddle River, N.J.: Pearson Education, 2009. J. Proakis and D. Manolakis, Digital Signal Processing, 3/e. Englewood Cliffs, N.J.: Prentice Hall, 1996. S. K. Mitra, Digital Signal Processing. A Computer-based Approach}, 2/e. Boston, MA: McGraw-Hill International, 2002. The student edition of MATLAB. The Mathworks C. S. Burrus, J. H. McClellan, A. V. Oppenheim, T. W. Parks, R. W. Schafer, and H. W. Schuessler, Computer-Based Exercises for Signal Processing. Englewood Cliffs, N.J.: Prentice-Hall, 1994. J. R. Buck, M. M. Daniel, and A. C. Singer, Computer Explorations in Signals and Systems Using MATLAB. Upper Saddle River, N.J.: Pearson Education, 1997.} J. G. Proakis and V. K. Ingle, Digital Signal Processing. Upper Saddle River, N.J.: Pearson Education, 2004. T. Dutoit and F. Marques, Applied Signal Processing. A MATLAB-Based Proof of Concept. New York, N.Y.: Springer, 2009 (πρόσβαση στο e-book μέσω του
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