• Recursive identification of time-varying Hammerstein systems with matrix forgetting 

  Dokoupil, Jakub; Václavek, Pavel (IEEE, 2023-05-01)

  The real-time estimation of the time-varying Hammerstein system by using a noniterative learning schema is considered and extended to incorporate a matrix forgetting factor. The estimation is cast in a variational-Bayes ...

• Measurement of thermal depolarization effects in piezoelectric coefficients of soft PZT ceramics via the frequency and direct methods 

  Fialka, Jiří; Beneš, Petr; Michlovská, Lenka; Klusáček, Stanislav; Pikula, Stanislav; Dohnal, Přemysl; Havránek, Zdeněk (Elsevier Ltd., 2016-09-01)

  Depolarization at high temperatures around the Curie point constitutes an important yet difficultly measurable material property of piezoelectric (PZT) ceramics. The common vibrometric technique (d33 meters) is not suitable ...

• Comparison of Methods for the Measurement of Piezoelectric Coefficients 

  Fialka, Jiří; Beneš, Petr (IEEE, 2013-04-03)

  The charge constant of piezoelectric material is one of the crucial constant values. At the present time, the measurement of this value is mostly realized by means of three techniques: the frequency method, the laser ...

• Confirmation of mathematical model of Helmholtz coils on the real construction 

  Uher, Miroslav; Vágner, Martin; Fialka, Jiří (DAAAM International Vienna, 2011-11-23)

  This paper deals with distribution of magnetic field inside paired coils in Helmholtz arrangement. Helmholtz coils consist of two separate coils. Their mutually arrangements is advantageous for generation of uniform magnetic ...

• Bayesian Inference of Total Least-Squares With Known Precision 

  Friml, Dominik; Václavek, Pavel (IEEE, 2022-09-06)

  This paper provides a Bayesian analysis of the total least-squares problem with independent Gaussian noise of known variance. It introduces a derivation of the likelihood density function, conjugate prior probability-density ...

• Adaptivity Schemes for Model Predictive Speed Control of PMSM 

  Kozubík, Michal; Václavek, Pavel; García de Madinabeitia, Iigo (IEEE, 2022-10-17)

  Model predictive control is a popular research topic in the field of motor control. Its direct way of implementing constraints and nonlinearities makes MPC a potential alternative to standard motor control approaches. On ...

• Improvement of the Temperature Stability of the Erbium-Doped Superfluorescent Fiber Source by Tuning the Reflectivity of the Fiber End 

  Skalský, Michal; Hnidka, Jakub; Havránek, Zdeněk (IEEE, 2023-03-15)

  A novel and simple way of improving the mean wavelength temperature stability of the erbium-doped superfluorescent source is described and demonstrated. We show that by introducing small reflectivity feedback at the unpumped ...

• Detection of the Interturn Shorts of a Three-Phase Motor Using Artificial Intelligence Processing Vibration Data 

  Doseděl, Martin; Kopečný, Ladislav; Kozovský, Matúš; Hnidka, Jakub; Havránek, Zdeněk (IEEE, 2022-12-07)

  The paper deals with description, design, learning and inference process of a convolutional 2D neural network for detection of shortened winding turns of a three-phase permanent magnet synchronous motor. Input datasets for ...

• A Heuristic Algorithm to Compute Multimodal Criterial Function Weights for Demand Management in Residential Areas 

  Kaczmarczyk, Václav; Fiedler, Petr; Bradáč, Zdeněk (MDPI, 2017-07-20)

  We present the conceptual design of a collective control scheme for appliances within a smart home. Based on the relevant energy acquisition procedures, three appliance groups are defined, modeled, and completed with an ...

• Optimal Scheduling of Domestic Appliances via MILP 

  Kaczmarczyk, Václav; Fiedler, Petr; Bradáč, Zdeněk (MDPI AG, 2015-01-08)

  This paper analyzes a consumption scheduling mechanism for domestic appliances within a home area network. The aim of the proposed scheduling is to minimize the total energy price paid by the consumer and to reduce power ...

• The Ideas of Industry 4.0: Seven Years After 

  Zezulka, František; Jirsa, Jan; Venkrbec, Lukáš; Marcoň, Petr; Benešl, Tomáš; Kaczmarczyk, Václav; Arm, Jakub; Bradáč, Zdeněk (ELSEVIER, 2022-05-19)

  The paper deals with a comparison of initial ideas of the Industry 4.0 activities and the state of the art of recent development of industrial production. Authors demonstrate their professional opinion that standardization ...

• An Experimental Training Production Line to Demonstrate the Basics of Industry 4.0 

  Marcoň, Petr; Jirsa, Jan; Venkrbec, Lukáš; Zezulka, František; Benešl, Tomáš; Kaczmarczyk, Václav; Arm, Jakub (ELSEVIER, 2022-05-19)

  The paper deals with appropriate possibilities, instrumentation, and technologies for purposes of education, presentation, teaching and research, and development of technologies and procedures of Industry 4.0 ideas, and ...

• In-Bed Posture Classification Based on Sparse Representation in Redundant Dictionaries 

  Mihálik, Ondrej; Sýkora, Tomáš; Husák, Michal; Fiedler, Petr (Elsevier, 2022-05-20)

  Non-orthogonal signal representation using redundant dictionaries gradually gained popularity over the last decades. Sparse methods find major application in signal denoising, audio declipping, time-frequency analysis, and ...

• Augmented Postprocessing of the FTLS Vectorization Algorithm - Approaching to the Globally Optimal Vectorization of the Sorted Point Clouds 

  Jelínek, Aleš; Žalud, Luděk (SciTePress, 2016-07-29)

  Vectorization is a widely used technique in many areas, mainly in robotics and image processing. Applications in these domains frequently require both speed (for real-time operation) and accuracy (for maximal information ...

• Brno Urban Dataset: Winter Extension 

  Ligocki, Adam; Jelínek, Aleš; Žalud, Luděk (Elsevier, 2022-01-01)

  This paper presents our latest extension of the Brno Urban Dataset (BUD), the Winter Extension (WE). The dataset contains data from commonly used sensors in the automotive industry, like four RGB and single IR cameras, ...

• Human Detection in Depth Map Created from Point Cloud 

  Ligocki, Adam; Žalud, Luděk (2022-04-02)

  This paper deals with human detection in the LiDAR data using the YOLO object detection neural network architecture. RGB-based object detection is the most studied topic in the field of neural networks and autonomous agents. ...

• Using an Automated Heterogeneous Robotic System for Radiation Surveys 

  Gábrlík, Petr; Lázna, Tomáš; Jílek, Tomáš; Sládek, Petr; Žalud, Luděk (2020-06-29)

  During missions involving radiation exposure, unmanned robotic platforms may embody a valuable tool, especially thanks to their capability of replacing human operators in certain tasks to eliminate the health risks associated ...

• Automatic Traffic Sign Detection and Recognition Using Colour Segmentation and Shape Identification 

  Horák, Karel; Číp, Pavel; Davídek, Daniel (EDP Sciences, 2016-08-01)

  The paper describes a colour-based segmentation method of European traffic signs for detection in an image and a feature-based recognition method for categorizing them into given classes. At first, we have performed analysis ...

• Models of pilot behavior and their use to evaluate the state of pilot training 

  Jirgl, Miroslav; Jalovecký, Rudolf; Bradáč, Zdeněk (Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, 2016-09-02)

  This article discusses the possibilities of obtaining new information related to human behavior, namely the changes or progressive development of pilots‘ abilities during training. The main assumption is that a pilot’s ...

• Application of High-Resolution 3D Scanning in Medical Volumetry 

  Chromý, Adam (Polish Academy of Sciences, 2016-03-30)

  This paper deals with application of 3D scanning technology in medicine. Important properties of 3D scanners are discussed with emphasize on medical applications. Construction of medical 3D scanner according to these ...

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