Fakulta elektrotechniky a informatiky / Faculty of Electrical Engineering and Informatics
Stálý URI pro tuto komunituhttps://hdl.handle.net/10195/3847
Práce obhájené před rokem 2008 jsou uloženy pouze v kolekci Vysokoškolské kvalifikační práce
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Konferenční objektpeer-reviewedpostprint Otevřený přístup Singularity subtraction in a multidimensional Fredholm integral equation of the second kind with a singular kernel(American Institute of Physics, 2019) Rak, JosefA numerical solution of the Fredholm integral equations can be obtained by many methods. Most of them lead to a solution of a system of linear equations with fully populated matrices. In the case of collocation or product integration methods, each element of the matrix is an integral, which needs to be calculated. It causes high computing time in multidimensional problems. Computing time can be reduced by the Nyström method. It is based on substitution of the integral by a numerical integration rule. It has the advantage that only diagonal elements of the matrix are integrals. When the kernel function is singular, a singularity subtraction is needed. However it can not be used for every kernel function and every integration rule. The main point of this paper is the convergence conditions of the Nyström method as applied to a special multidimensional integral equation. The paper includes an illustrative example.Konferenční objektpeer-reviewedpostprint Otevřený přístup Adaptive Pulse Compression Filter in Radar Receiver Application(IEEE (Institute of Electrical and Electronics Engineers), 2019) Bezoušek, Pavel; Karamazov, Simeon; Roleček, JiříIn the paper the matched compression filter, the compression filter with minimum sidelobe energy and with maximum peak to sidelobe ratio for linear and nonlinear frequency modulated signals are presented and compared. Then application of those filters in radars in various clutter situations are discussed.Konferenční objektpeer-reviewedpostprint Otevřený přístup Nonlinear distortion in a microwave high power amplifier(IEEE (Institute of Electrical and Electronics Engineers), 2019) Bezoušek, Pavel; Matoušek, David; Rejfek, LubošIn this paper the high-power amplifier CGHV31500F designed for the radar S-Band application is studied. The amplifier module is based on GaN HEMT encapsulated internally matched transistor, delivering more than 500 W in a pulse regime. Nonlinear model of this amplifier was developed and nonlinear distortion of a standard radar signal and of possible future QAM signals are predicted.Konferenční objektpeer-reviewedpostprint Omezený přístup MONDAY EFFECT ON STOCK PRICES: TESTING OF STATISTICAL HYPOTHESIS(Slovenská technická univezita v Bratislave, 2019) Pozdílková, AlenaThe aim of this article will be to analyse one of calendar effects - Monday effect. In testing, we will not just go through analysing price returns, but we will study the values of the measurement of investment success. Therefore, we will determine the Win Ratio, Profit Factor, and Profit Loss Ratio. For hypothesis testing, we suggest appropriate statistical tests. We will work with the prices of the period from January 2005 to October 2018 for 29 stock companies that are part of the DJA index.Konferenční objektpeer-reviewedpostprint Omezený přístup Normy a praxe(Technická univerzita v Košiciach, 2019) Taufer, Ivan; Vítečková, Miluše; Víteček, Antonín; Javůrek, MilanV příspěvku je poukázáno na rozpory v terminologii mezi ČSN IEC 60050-351+A1 a ČSN EN 60027-6 a užívaným, historicky ustáleným názvoslovím. Nesrovnalosti lze přičíst již nedbale zpracované původní normě a hlavně neodbornému překladu z anglického originálu. V seznamu vybraných citací je tento rozdíl názorně dokumentován.Konferenční objektpeer-reviewedpostprint Omezený přístup Dva programy pro vyhodnocování experimentálních dat(Technická univerzita v Košiciach, 2019) Javůrek, Milan; Taufer, Ivan; Merta, JanV příspěvku jsou popsány dva programy pro statistické zpracování experimentálních dat s pracovním názvem TestNorm a NelReg, vypracované jako podpůrné učební pomůcky. Program TestNorm je určen pro zjišťování normality dat, program NelReg pro regresi nelineární funkce. Prezentované programy mají jednoduchou obsluhu a přívětivé vizuální prostředí.Konferenční objektpeer-reviewedpostprint Otevřený přístup Comparison of ReLU and linear saturated activation functions in neural network for universal approximation(IEEE (Institute of Electrical and Electronics Engineers), 2019) Štursa, Dominik; Doležel, PetrActivation functions used in hidden layers directly affect the possibilities for describing nonlinear systems using a feedforward neural network. Furthermore, linear based activation functions are less computationally demanding than their nonlinear alternatives. In addition, feedforward neural networks with linear based activation functions can be advantageously used for control of nonlinear systems, as shown in previous authors' publications. This paper aims to compare two types of linear based functions - symmetric linear saturated function and the rectifier linear unit (ReLU) function as activation functions of the feedforward neural network used for a nonlinear system approximation. Topologies with one hidden layer and the combination of defined quantities of hidden layer neurons in the feedforward neural network are used. Strict criteria are applied for the conditions of the experiments; specifically, the Levenberg-Marquardt algorithm is applied as a training algorithm and the Nguyen-Widrow algorithm is used for the weights and biases initialization. Three benchmark systems are then selected as nonlinear plants for approximation, which should serve as a repeatable source of data for testing. The training data are acquired by the computation of the output as a reaction to a specified colored input signal. The comparison is based on the convergence speed of the training for a fixed value of the error function, and also on the performance over a constant number of epochs. At the end of the experiments, only small differences between the performance of both applied activation functions are observed. Although the symmetric linear saturated activation function provides the lesser median of the final error function value across the all tested numbers of neurons in topologies, the ReLU function seems to be also capable of use as the activation function for nonlinear system modeling.Konferenční objektpeer-reviewedpostprint Otevřený přístup Convolutional Neural Network for Sound Processing - Study of Deployed Application(IEEE (Institute of Electrical and Electronics Engineers), 2019) Doležel, Petr; Štursa, Dominik; Honc, DanielPest birds are considered as a special kind of vermin, since, in most of countries, their legal position does not enable their direct extermination. Therefore, in order to protect the agricultural areas indirectly from pest birds, the robust and highly selective pest bird sensor is necessary to design. In this contribution, the pest bird detection unit, based on a convolutional neural network, is presented. The convolutional neural network itself is used for the decision making about the pest bird occurrence, while sound recordings are used as input data. The testings, presented at the end of the contribution, proved a very high accuracy of the detection unit, with the results indispensably improved in comparison to previously presented approaches.Konferenční objektpeer-reviewedpostprint Otevřený přístup On possibilities of human head detection for person flow monitoring system(Springer Nature Switzerland AG, 2019) Doležel, Petr; Štursa, Dominik; Škrabánek, PavelAlong with the development of human society, economy, industry and engineering, as well as with growing population in the world's biggest cities, various approaches to person detection have become the subject of great interest. One approach to developing a person detection system is proposed in this paper. A high-angle video sequence is considered as the input to the system. Then, three classification algorithms are considered: support vector machines, pattern recognition neural networks and convolutional neural networks. The results showed very little difference between the classifiers, with the overall accuracy more than 95% over a testing set.Konferenční objektpeer-reviewedpostprint Otevřený přístup Bin Picking Success Rate Depending on Sensor Sensitivity(IEEE (Institute of Electrical and Electronics Engineers), 2019) Doležel, Petr; Pidanič, Jan; Zálabský, Tomáš; Dvořák, MiroslavThe goal of this contribution is to determine correlation between an applied sensor for object registration and the success rate of the bin-picking problem. In most applications of a bin picking problem in industry, the procedure consists of two consecutive steps. The first step provides an initial guess of both position and rotation angle of the object to be registered, while the second one improves the exact pose accuracy, as required in following tasks. The second step can be, among others, implemented by the Iterative Closest Point Algorithm (ICP). It is well known that the ICP algorithm is very sensitive to the initial guess of the position and rotation angle of the object. Another interesting feature, especially from the technician’s point of view, is the sensitivity of the ICP algorithm in relation to the applied sensor. Therefore, one particular bin picking application, involving complex irregular objects, is examined in this paper. Various kinds of sensors for 3D scene reconstruction are employed and, as a result of this contribution, a comprehensive set of relations between sensor quality and the ICP algorithm sensitivity is formulated.
