Digital Signal Processing

Higher education teachers: Burnik Urban

Subject description

Prerequisits:

• Completed courses in Mathematics I, II and Signals and Informations

Content (Syllabus outline):

Fundamentals of digital signals (signals, phasors, the building blocks for digital signal processing, 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). Quantized signal (analog-to- digital conversion, quantisers, quantization error, quantization and digital filtering). Digital sound and image processing. Transformations of multidimensional signals. Compression of sound, image and video signals.

Objectives and competences:

Learning about 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. Knowing the basic procedures for digital recording, processing and compression of sound and images.

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

Readings:

1. Manolakis, Ingle, Applied Digital Signal Processing, Cambridge University Press, 2011
2. Bose, T., Digital signal and image processing, John Wiley and Sons, 2004.