Signals and Systems

This lesson introduces the principles of analyzing and studying signals and systems, providing the knowledge for the design of systems (voice and picture processing, telecommunication systems, automation systems, robotics, etc) and providing the means for the understanding contemporary complex systems and their modelling. The main properties of signals and systems are introduced in the context of the lesson, giving emphasis to the linear time invariant systems, together with Fourier, Laplace and Z transformations.


The course aims to give the student a general and introductory overview of signals in relation to the systems that produce them, especially focusing on linearly. This is basic knowledge for designing systems (voice processing, image processing, telecommunication systems, automation systems, robotics, etc.) And helps both in understanding today's complex systems, but also in their modeling. At the end of the course students should be able to know: • Key concepts and continuous signals and discrete-time systems • Basic properties of systems and properties of linear time-invariant systems. • Basic properties of Fourier transforms • The concepts of linear and circular convolution. • The fast Fourier transform. • The transformation z and Laplace transform.




Key concepts of continuous and discrete time signals and systems Concepts of stagnation Stability Systems Basic properties of Fourier transforms and orthogonal transforms The concepts of linear and circular convolution Fast Fourier transform Z transformation and transformation of Laplace Difference Equations. Frequency response Transfer function and execution systems Sampling ideal and real, theorem of Nyquist Lowpass filters State variables and performance of the system. Theory of random signal






Instructors: Christos Michalakelis
Department: Informatics and Telematics
Institution: Harokopio University of Athens
Subject: Computer Science, Information Technology, Telecommunications
Rights: CC - Attribution-NonCommercial

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