Basic definitions of signals and systems, periodic signals, unit step function, impulse function. Categories of systems, static and dynamic systems, causal and non-causal systems, linear and non-linear systems, time invariant and variant systems. Impulse response of linear systems. Convolution properties. Stability of systems. Direct and inverse Fourier transform. Convergence and properties of the Fourier transform. Application of the Fourier transform in the study of linear systems, system frequency response, description of Linear Time Invariant (LTI) systems with differential equations and the Fourier transform, ideal lowpass filter. Fourier series, Fourier series of periodic functions, Fourier series for even or odd symmetry, Parseval’s theorem. Laplace transform, properties and theorems. Inverse Laplace transform. Bilateral Laplace transform. Use of the Laplace transform for solving linear differential equations. Use of the Laplace transform in the analysis of linear systems and the study of their stability. Discrete-time signals and systems, direct and inverse Z transform and its properties. Unilateral Z transform. Discrete-time Fourier transform. Sampling – Nyquist theorem. Discrete Fourier transform.

Upon completion of the course, the student will be able to:

• understand basic system properties such as linearity, causality, stability, etc.
• use basic functions, such as exponential and trigonometric, to represent physical signals
• describe the relation between systems and signals through mathematical tools such as differential equations, difference equations, convolutional sum and integral, frequency response, etc.
• compute the output signal from the input signal and the system's mathematical model
• describe mathematically the composition of systems from simpler ones
• understand intuitively the analysis and processing of signals in the frequency domain
• understand the sampling process and the relationship between continuous and discrete-time signals
• use the MATLAB software to solve problems of linear systems and signals

Not required.

• Book [102071800]: Σήματα και Συστήματα Συνεχούς και Διακριτού Χρόνου με Matlab και Octave, 3η Έκδοση, Παρασκευάς Μιχάλης
• Book [112705601]: Σήματα και Συστήματα με τη χρήση του MATLAB, Luis F. Chaparro, Aydin Akan
• Book [31326]: Εισαγωγή στη θεωρία σημάτων και συστημάτων, Θεοδωρίδης Σέργιος, Μπερμπερίδης Κώστας, Κοφίδης Λευτέρης

Additional teaching material:

• Book [320174]: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ, ΣΕΡΑΦΕΙΜ ΚΑΡΑΜΠΟΓΙΑΣ

          https://repository.kallipos.gr/bitstream/11419/2992/3/Signal_and_Systems_22_11_2015-KOY.pdf

IEEE Signal Processing Magazine, https://signalprocessingsociety.org/publications-resources/ieee-signal-processing-magazine 

IEEE Signal Processing Letters, https://signalprocessingsociety.org/publications-resources/ieee-signal-processing-letters 

IEEE Transactions on Signal Processing, https://signalprocessingsociety.org/publications-resources/ieee-transactions-signal-processing 

Lectures, resolving exercises, laboratory exercises

Practical training in the laboratory through laboratory exercises

Assignment (laboratory) - 15% of the final grade

Final written exam - 85% of the final grade

Detailed information regarding the conduct and evaluation of the course can be found in the course e-class (https://eclass.icsd.aegean.gr/courses/ICSD464/) and in the first presentation of the course.

Face-to-face