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Signal Processing – Laboratory for Machine Intelligence

Signal Processing

Study program: Electrical Engineering, 1st bologna cycle
Semester: winter semester
Credits: 6

Lecturer: Assoc. Prof. Vitomir Štruc, PhD
Assistant: Asst. Marija Ivanovska, MSc


Course aims

Students learn about representations and characteristics of signals that can be represented as either (complex) deterministic functions or random functions of time and/or frequency. The students acquire knowledge about different signal types, signal descriptions and processing methods.

Content

The course lectures cover the most important topics from the area of signal processing:

  • Introduction: basic definitions, short history of the signal processing theory, position of the signal processing theory in electrotechnical and other sciences.
  • Signals classification: signals with finite energy and finite average power, periodical a-periodical, deterministic and random signals.
  • Signals representations: the use of the signals representations, types of representations and representations, quality measures, examples of basic function sequences.
  • Frequency analysis: Fourier series and Fourier transform.
  • Random signals: approaches to the random signal processing, stationary random process, correlation and covariance functions, sampling and time averages, ergodicity.
  • Signals correlation and convolution: correlation and convolution definitions and properties for different types of signals, similarity measures, random signal spectrum evaluations, convolution and linear stationary systems, detection of periodic components in combinations of signals.
  • Sampling and quantization: purpose of the sampling and quantization, sampling theorem, representation of sampling and reconstruction, types of quantization, quantization error signal and its properties, quantization examples.
  • Digital signal processing: discrete Fourier transform.

Literature

Basic literature in Slovene

  • Mihelič, F., Signali, Založba FE in FRI, 2006
  • Mihelič, F., Gyergyek, L., Ebenšpanger, T., Signali – Priročnik z zbirko rešenih nalog, 3 izdaja, Založba FE in FRIm Ljubljana, 2009

Basic literature in English

  • V. Štruc, Laboratory Assignments for Signal Processing – Workbook, e-book, First Edition, Ljubljana, 2015.

Alternatives in English

  • Haykin , S. S., Van Veen , B.: Signals and Systems, Wiley, 2003.
  • Phillips, C. L., Parr, J. M., Riskin, E. A.: Signals, Systems and Transforms, Prantice Hall, 2003.
  • Gray, R. M., Davisson, L. D.: An Introduction to Statistical Signal Processing, Cambridge University Press, 2004.
  • Ifeachor, E. C., Jervis, B. W.: Discrete transforms, Digital Signal Processing – A practical Approach, Prentice Hall, 2002.

Freely available literature in English

  • Orfanidis S.J.: Introduction to Signal Processing, Copyright (c) 2010 S.J. Orfanidis. [website][PDF]
  • Orfanidis S.J.: Optimum Signal Processing, Copyright (c) 1996 S.J. Orfanidis. [website][PDF]
  • Gray, R.M. and Davisson L.D.: Introduction to Statistical Signal Processing [website]

Prerequisites

Basics of mathematical analysis, algebra and probability theory.

Additional information

More information on the course as well as material needed for the lab assignments is available from the E-classroom.

Duties of exchange students

In the winter semester 2018 exchange students need to fulfil the following duties to finish the course:

  • solve all homework given by the  professor,
  • attend and successfully finish all lab assignments,
  • take the oral exam.