Institute of Information Theory and Automation

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Dept.: SI Duration: 2022 - 2024
The project deals with the development of active fault diagnosis (AFD) algorithms for stochastic discrete-time large-scale systems. To achieve the feasibility of the algorithms, tensor decompositions (TDs) will be employed in several components of the AFD algorithm design. In particular, the TDs will be applied for the dynamic programming responsible for the active aspect of the diagnosis, for...
Dept.: SI Duration: 2017 - 2019
Dept.: SI Duration: 2014 - 2016
The word “TENSOR” in this project is understood as a multidimensional linear array of a rectangular shape, whose entries are either real or complex numbers. Such data structures are encountered, e.g., in chemometrics, telecommunication, biomedicine (fMRI, EEG) , data mining, kinetic theory of descriptions of materials, and so on. Canonical polyadic (CP) decomposition is a decomposition of a...
Dept.: SI Duration: 2009 - 2013
The proposed project aims at development of existing methods of blind source separation and blind separation of convolutive mixtures that are important in biomedicine, acoustics and speech processing, and in wireless communications. It will extend previous results of the appplicants in this area. In particular, goals of the project include design of computationally effective methods of...