Digital Signal Processing

Higher education teachers: Umek Anton
Credits: 6
Semester: summer
Subject code: 64174

Subject description


  • Knowledge covered by courses Mathematics I-IV and Continuous signals and systems.

Content (Syllabus outline):

Fundamentals of time-diskretel signals (signals, signal classification, time and frequency space). Sampling (sampling theorem, effects of sampling in time and frequency domain). Discrete-time systems (linear time- invariant discrete systems, causality, differential equations and discrete linear systems, impulse response , the discrete - time systems structure, implementation) . Frequency analysis of discrete - time signals. Discrete Fourier transform (Fast Fourier transform algorithms, fast discrete filtering using FFT). Z-transform (Z transform and inverse Z transform , application in digital signal processing , rational Z transform, time behaviour and roots of rational Z transform) . Analysis and synthesis of discrete time systems in frequency domain (transfer function of the system, analysis of systems with rational Z transfer function, stability, frequency response). Digital filter design (finite response filters, the infinite response filters). Random signal generators (uniform distribution, Gaussian white noise). Signal quantisation (analog-to- digital conversion, quantisers, quantization errors).

Objectives and competences:

Knowing the basic tools for digital signal processing. Understanding the processes and consequences of capture, analysis and signal processing in discrete - digital form and their reconstruction back to the analog domain. Competence for the selection of a suitable method of digital signal acquisition, understanding the implications of digitalisation and understanding the basic signal analysis in time and frequency domain. The ability to use basic systems for digital filtering and signal enhancement. Understanding digital signal processing as a building block of complex digital communication devices.

Intended learning outcomes:

Understanding of digital signals in the time and frequency domain, fundamental applicative knowledge of digital filters and systems.

Learning and teaching methods:

  • Lectures with DSP theory and practically oriented lab assignments encouraging teamwork.

Study materials

John G. Proakis, Dimitris K. Manolakis, Digital Signal Processing (4th Edition) Prentice Hall; 4 edition, 2006

Study in which the course is carried out

  • 3 year - 1st cycle - Electrical Enginnering - Information and Communication Technologies