Signals and Systems

Course Code: Ν2-5050Β
Weekly Duty: 4 (2Th + 2L)
ECTS: 5
Typical Semester: 5th
Course Category: Special Infrastructure Course
Prerequisites:  

Learning Outcomes

Upon successful completion of this course the student will be able to:

  • know how to describe a signal in an analytic way, to classify signals and to describe their properties in the field of continuous or discrete time (periodic, exponential, stochastic, deterministic, with symmetries)
  • analyze and classify systems based on their properties (linearity, time invariance, causality, memory, stability, inversibility)
  • analyze, represent, design, approximate and manage signals using a computer (capacity acquired mainly from the laboratory part of the course)
  • represent linear time-invariant (LTI) systems with equations, with block diagrams, with their impulse response or with their transfer function and to understand the equivalence of these representations
  • understand the new arithmetic operation of convolution of two signals and to appreciate its importance in the analysis of LTI systems
  • understand the relationship between the time and frequency domains and to appreciate the importance of Fourier analysis (in both, the continuous and discrete time domains)
  • understand the convolution theorem and the basic properties of Fourier transform
  • understand the sampling theorem, the relation of the frequency spectra of the sampled signal and the original analog signal and the relationship between aliasing and sampling
  • be familiar with the Matlab environment and the signal processing toolbox

Course Content

The concepts of signals and systems. Categories and properties of signals (analog, digital, real, complex, kinds of symmetry, periodic, exponential, stochastic, deterministic, energy signals, power signals). System representation and properties (linearity, time invariance, causality, memory, stability, inversibility). The telecommunication system and its subsystems. Mathematical operations on signals. Signal modulation. Elementary signals (step function, square and triangular pulse, unit impulse). Linear Time-Invariant (LTI) Systems. Impulse response. Convolution. Correlation. Block diagrams. Sampling. Shannon theorem. Nyquist frequency. Aliasing. Fourier Series. Fourier transform. Properties of Fourier transform. Transfer function. Discrete Fourier transform. Example of processing analog signals on a digital computer using the discrete Fourier transform. Applications. Laboratory in MATLAB environment using the Signal Processing Toolbox.

Literature
  1. Παλαμίδης Αλ., Βελώνη Αν., Σήματα & Συστήματα με MATLAB, Σύγχρονη Εκδοτική, 2008.
  2. Θεοδωρίδης Σ., Μπερμπερίδης Κ., Εισαγωγή στη Θεωρία Σημάτων και Συστημάτων, Εκδόσεις Τυποθήτω, 2002.
  3. Βασιλάς Ν., Σήματα και Συστήματα, Διδακτικές Σημειώσεις, ΤΕΙ Αθήνας, 2004.
  4. Καραγιάννης Γ., Καλλίνικος Δ., Σήματα και Συστήματα με έμφαση στο διακριτό χρόνο, Εκδόσεις Συμεών, 1991.
  5. Boulet B., Fundamentals of Signals and Systems, Da Vince Engineering Press, 2006.
  6. Lathi B.P., Linear Systems and Signals, 2nd ed., Berkeley Cambridge Press, 2001.
  7. Kamen E., Heck B., Kamen E., Fundamentals of Signals and Systems: With MATLAB Examples, Prentice Hall, 2000.
  8. Haykin S., Van Veen B., Signals and Systems, John Wiley and Sons, 1999.
  9. Soliman S.S., Srinath M.D., Continuous and Discrete Signals and Systems, 2nd ed., Prentice Hall, 1997.
  10. Oppenheim A.V., Willsky A.S., Nawab S.H., Signals and Systems, 2nd ed., Prentice Hall, 1996.

Internationalisation I18n