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Institution

University of Maribor

EducationMaribor, Slovenia
About: University of Maribor is a education organization based out in Maribor, Slovenia. It is known for research contribution in the topics: Population & KEKB. The organization has 3987 authors who have published 13077 publications receiving 258339 citations. The organization is also known as: Univerza v Mariboru.


Papers
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Journal ArticleDOI
TL;DR: Continuous adsorption measurements show that silica aerogels are excellent adsorbents of BTEX vapours from waste gas stream.

77 citations

Journal ArticleDOI
TL;DR: It can be concluded that males and females differ in the local as well as long range coding of information - the binding of distributed responses - aswell as in the excitability dynamics of their cortical network.

77 citations

Journal ArticleDOI
TL;DR: It is proved that the graphs S (n, κ) possess unique 1-perfect codes, thus extending a previously known result for Hn, and an efficient decoding algorithm is presented.
Abstract: Sierpinski graphs S (n, κ) generalise the Tower of Hanoi graphs—the graph S (n, 3) is isomorphic to the graph Hn of the Tower of Hanoi with n disks. A 1-perfect code (or an efficient dominating set) in a graph G is a vertex subset of G with the property that the closed neighbourhoods of its elements form a partition of V (G). It is proved that the graphs S (n, κ) possess unique 1-perfect codes, thus extending a previously known result for Hn. An efficient decoding algorithm is also presented. The present approach, in particular the proposed (de)coding, is intrinsically different from the approach to Hn.

77 citations

Book ChapterDOI
09 Sep 2007
TL;DR: In this article, a gradient-based method for robust assessment of the sparse pulse sources, such as motor unit innervation pulse trains in the filed of electromyography, was proposed.
Abstract: This paper introduces gradient based method for robust assessment of the sparse pulse sources, such as motor unit innervation pulse trains in the filed of electromyography. The method employs multichannel recordings and is based on Convolution Kernel Compensation (CKC). In the first step, the unknown mixing channels (convolution kernels) are compensated, while in the second step the natural gradient algorithm is used to blindly optimize the estimated source pulse trains. The method was tested on the simulated mixtures with random mixing matrices, on synthetic surface electromyograms and on real surface electromyograms, recorded from the external anal sphincter muscle. The results prove the method is highly robust to noise and enables complete reconstruction of up to 10 concurrently active motor units.

76 citations

Journal ArticleDOI
TL;DR: A novel predictive variable-structure-switching-based current controller for a three-phase load driven by a power inverter that is suitable for different types of ac loads and ac motors and a new logical FPGA torque and speed controller is developed.
Abstract: This paper proposed a novel predictive variable-structure-switching-based current controller for a three-phase load driven by a power inverter. The design specifications are robustness to load electrical parameters, fast dynamic response, reduced switching frequency, and simple hardware implementation. In order to meet previous specifications, a sliding mode controller has been developed, which is designed as finite-state automata, and implemented with a field-programmable gate array (FPGA) device. The switching strategy implemented within the state transition diagram provides for a minimum number of switches by the three-phase inverter that is confirmed through simulation and experimental results. Its regulation using the proposed control law provides good transient response by the brushless ac motor control. However, this does not limit the wider applicability of the proposed controller that is suitable for different types of ac loads (rectifier and inverter) and ac motors (induction, synchronous, and reluctance). A new logical FPGA torque and speed controller is developed, analyzed, and experimentally verified.

76 citations


Authors

Showing all 4077 results

NameH-indexPapersCitations
Ignacio E. Grossmann11277646185
Mirjam Cvetič8945627867
T. Sumiyoshi8885562277
M. Bračko8773830195
Xin-She Yang8544461136
Matjaž Perc8440022115
Baowen Li8347723080
S. Nishida8267827709
P. Križan7874926408
S. Korpar7861523802
Attila Szolnoki7623120423
H. Kawai7647722713
John Shawe-Taylor7250352369
Matjaz Perc5714812886
Mitja Lainscak5528722004
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202352
2022135
2021809
2020870
2019832
2018756