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Use of HRV analysis for automatic detection of ischemia in animal isolated heart
Vykoupil, Pavel ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This paper deals with HRV analysis, creating segments for this analysis, calculating HRV parameters and their classification for automatic detection of ischemia. First part of the work is dedicated to theoretical describtion of heart anatomy, ECG reading, its processing and methods of HRV analysis. Next part of this work outline the principle of creating segments used for calculation of HRV parameters. Last part of the work indtroduces classification of said parameters with the help of multilayered neural networks and finding their best possible setup based on least classification error and computing time achieved. Calculation of HRV parameters and classification was realized using software Matlab.
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Convolutional neural network for image processing
Krajčovičová, Mária ; Rajmic, Pavel (referee) ; Burget, Radim (advisor)
Goal of this Diploma thesis was Convolutional neural network investigation in last years. Diploma thesis also contains information about designing of appropriate Convolutional neural network models and implementation of these models in Java programming language. Result of the thesis are comparison and evaluation of results which were reached from implemented application.
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Design of Switch Used in Modern Communication Networks
Mojžiš, Ľubomír ; Novotný, Bohumil (referee) ; Škorpil, Vladislav (advisor)
This diploma thesis deals with switching components of modern communication networks. A switch architecture focused on the quality of service is described in this paper and there are two switch models designed and simulated in the simulating program MATLAB-SIMULINK. The first model is based on classic switching and the other one is controlled by neural network. A laboratory exercise suitable for communication networks education is created in this paper on the basis of designed models.
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Artificial neural network RCE
Maceček, Aleš ; Klusáček, Jan (referee) ; Jirsík, Václav (advisor)
This paper is focused on an artificial neural network RCE, especially describing the topology, properties and learning algorithm of the network. This paper describes program uTeachRCE developed for learning the RCE network and program RCEin3D, which is created to visualize the RCE network in 3D space. The RCE network is compared with a multilayer neural network with a learning algorithm backpropagation in the practical application of recognition letters. For a descriptions of the letters were chosen moments invariant to rotation, translation and scaling image.
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Data Mining
Stehno, David ; Hynčica, Tomáš (referee) ; Honzík, Petr (advisor)
The aim of the thesis was to study and describe data mining methodology CRISP-DM. From the collected database of calls to the call center a prediction was performed, based on CRISP-DM methodology. In phase of test situation modeling four different testing methods were used: the k-NN, neural network, linear regression and super vector machine. The input attributes importance for further prediction was evaluated based on different selections. The results and findings may provide data for further more accurate forecasts in the future; not only in number of calls but also other indicators relevant to the call center.
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The use of artificial intelligence in cryptography
Lavický, Vojtěch ; Rosenberg, Martin (referee) ; Babnič, Patrik (advisor)
Goal of this thesis is to get familiar with problematics of neural networks and commonly used security protocols in cryptography. Theoretical part of the thesis is about neural networks theory and chooses best suitable type of neural network to use in cryptographic model. In practical part, a new type of security protocol is created, using chosen neural network.
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Analysis of AVG signals
Mikauš, Jakub ; Čížek, Martin (referee) ; Rozman, Jiří (advisor)
MIKAUŠ, J. Analysis of AVG signals. Brno: Brno University of Technology,The Faculty of Electrical Engineering and Communication, 2008. 33 s., 1 příl. Supervisor of bachelors’s thesis doc. Ing. Jiří Rozman, CSc. This thesis deals with AVG (arteriovelocitogram) signals analysis, that’s gained non-invasive measurment by the help ultrasound diagnostic equipments. The gained data of these signals are make use of specify diagnosis patients with ischemic disease. For this analysis is take advantage of algorithm using neural network of program enviroment MatLab. Variety topologies of multiply neural network were verified and results evaluated.
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Electromagnetic analysis
Kolofík, Josef ; Reichert, Pavel (referee) ; Martinásek, Zdeněk (advisor)
This thesis deals with electromagnetic analysis and applications of electromagnetic side channel. The first and second part describes the basics of cryptography, function of cryptographic module and side-channel attacks. The third part discusses the electromagnetic analysis, construction of probe, a description of the laboratory workplace, the electromagnetic emission of PIC16F84A, AES and preparation for laboratory measurements. The fourth part describes specific laboratory measurements and extracting the useful signal. In the fifth part of the thesis presents the results of processing the measured values, the outputs generated by scripts and found the link between measured curves and AES encryption key. In the sixth part of the thesis are analyzed the basics of defense against side channel attack.
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Side channels
Kolařík, Jan ; Sobotka, Jiří (referee) ; Martinásek, Zdeněk (advisor)
This Master Thesis deals with the side channels, AES encryption algorithm and the use of neural networks to obtain the encryption key. The first part of this work is focused on the basics of cryptography and attacks on cryptographic module. The second part is focused on electromagnetic side channel attack on PIC16F84A microcontroller with embedded AES algorithm. In this section, the Master Thesis tries to analyze electromagnetic emissions of operation S-Box in AES algorithm and try to find sensitive information to use neural network identify encryption key of the AES algorithm. In conclusion is described the software source code to determine the encryption key, summarized results and discussed ways to defend against electromagnetic side channel attack.
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FPGA implementation of artificial neural network
Čermák, Justin ; Šteffan, Pavel (referee) ; Bohrn, Marek (advisor)
This master's thesis describes the design of effective working artificial neural network in FPGA Virtex-5 series with the maximum use of the possibility of parallelization. The theoretical part contains basic information on artificial neural networks, FPGA and VHDL. The practical part describes the used format of the variables, creating non-linear function, the principle of calculation the single layers, or the possibility of parameter settings generated artificial neural networks.
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