Our group focuses on the research, development and implementation of advanced digital signal and image processing algorithms, mainly in the fields of telecom, audio processing and scene analysis (image segmentation, motion detection). We build on our experience with the Bayesian approach to recursive identification of linear systems with time variable parameters.
Our target platforms are Field- Programmable Gate Arrays (FPGAs). We use mostly Matlab/Simulink to specify, model and verify algorithms which we subsequently convert and synthesize to FPGAs. These specialized HW solutions are likely to be used in embedded systems. That is why we also study features which result in fast execution, small memory footprint, small chip area and low power consumption. This is achieved through designing new DSP algorithms or modifying the existing DSP algorithms and by exploiting advanced architectural properties of FPGA circuits.
Our aim is not only to deal with the theoretical design of algorithms but also to help industrial partners to solve implementation issues in all their complexity.
Our department participated in several RTD projects supported by Framework Programmes of the EU as well as national grant agencies. Nowadays our group takes part in five projects and pilot lines financed by ARTEMIS and ENIAC Joint Undertakings.
The scientific profile is complemented with activities which promote cooperation between academia and industry. This work is realized in the frame of the project OKO ICT Branch Contact
After 15 years the most prominent European conference on programmable logic comes back to the Czech Republic.
Organized by UTIA with the help of other major Czech universities active in this area, it will take place in Prague from August 31 to September 2, 2009.
For more details visit the main conference web site at
Our group focuses on the research, development and implementation of advanced digital signal processing algorithms, mainly in the fields of adaptive control and audio processing. We build on our experience with statistics, namely with the Bayesian approach to system identification and modeling, as well as with the relevant fields of linear algebra.
Responsible for information: ZS Last modification: 17.02.2015