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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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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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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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The new side channels in cryptography
Machů, Petr ; Stančík, Peter (referee) ; Martinásek, Zdeněk (advisor)
This thesis is focused on the side-channels in the cryptology. The main attention is paid to the side-channels, which allow an attack on a computer keyboard. Especially the acoustic side-channel is focused on. Through this channel are demonstrated two attacks on the keyboard. At first, the method of recognizing is described. The neural network was used for the recognition. Then, the demonstration attacks on the keyboard are described. The first demonstration is an attack in laboratory conditions and the other in terms of household conditions. The thesis describes two attacks from the record, through data recognition by neural networks to evaluate the actual demonstration of attack. The following describes the recommendations for disabling attack. The results are supplemented by graphs and discussed.
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Optical processing of questionnaires
Nožka, Tomáš ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
This master thesis deals with the principles of form design, form printing and form processing. Three different types of forms and applications for their detection are created with the reference of these principles. This application provides to create a new type of form and to print out a form. The application itself is implemented in C++ with the use of OpenCV library. This work describes the classification methods of direction finding marks, identification numbers and submission numbers, bar codes EAN-13, page numbers, answer fields and single answers. The classification of all the handwritten numbers is implemented by neural nets.
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Hand gesticulation recognition in image
Mráz, Stanislav ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
This master’s thesis is dealing with recognition of an easy static gestures in order to computer controlling. First part of this work is attended to the theoretical review of methods used to hand segmentation from the image. Next methods for hang gesture classification are described. The second part of this work is devoted to choice of suitable method for hand segmentation based on skin color and movement. Methods for hand gesture classification are described in next part. Last part of this work is devoted to description of proposed system.
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Cryptanalysis using neural networks
Budík, Lukáš ; Mačák, Jaromír (referee) ; Martinásek, Zdeněk (advisor)
This dissertation deals with analysis of current side canal by means of neural network. First part describes basis of cryptografy and dilemma of side canal. In the second part is theoretickly described neural network and correlative analysis. Third part describes practical analysis of calibres of current side canals by means of classifier which uses neural network in Matlab surrounding. This classifier is confronted with classifier which uses correlative analysis.
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Adaptive controllers with principles of artificial intelligence and its comparison with classical identifications methods
Vaňková, Tereza ; Dokoupil, Jakub (referee) ; Pivoňka, Petr (advisor)
Master’s thesis is focused on the adaptive controllers. The first theoretic part mainly describes the parametric identification, which belongs to the most important part of the adaptive controller’s structure. Classical identification methods (the recursive least squares methods) are firstly mentioned and afterwards the identification methods based on the neural network (the Marquardt-Levenberg algorithm and the new identification algorithm NIA inspired by the neural networks) are described. At the conclusion of the theoretic part there are mentioned the algorithm of the adaptive controller’s tuning which uses the identification parameters (the modified Z-N method) and the tested types of adaptive controllers. Particular results, which were found out by verifying of the adaptive controllers on the simulation and real models, are contained in second, the practical, part of the thesis. Finally, achieved results are compared with the classical discrete PID controller and with the adaptive controller of the B&R company.
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