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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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Fuzzy Neural Networks for Pattern Classification
Ollé, Tamás ; Raida, Zbyněk (referee) ; Vágnerová, Jitka (advisor)
Práce popisuje základy principu funkčnosti neuronů a vytvoření umělých neuronových sítí. Je zde důkladně popsána struktura a funkce neuronů a ukázán nejpoužívanější algoritmus pro učení neuronů. Základy fuzzy logiky, včetně jejich výhod a nevýhod, jsou rovněž prezentovány. Detailněji je popsán algoritmus zpětného šíření chyb a adaptivní neuro-fuzzy inferenční systém. Tyto techniky poskytují efektivní způsoby učení neuronových sítí.
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Classification of ECG by artificial neural networks
Loviška, David ; Vítek, Martin (referee) ; Hrubeš, Jan (advisor)
The aim of project with name Classification ECG by artificial neural networks is simplify and speed up working a doctor. That reaches created program that the is capable simply and almost at once classify EKG signal using artificial neuronal nets. Created program will give to the doctor basic information about used electrocardiogram, as are time period and amplitude signal in single surveyed sections. Subsequently will program warn doctor about abnormalities from normal. Part of program is also graphic window with painted signal and on him in color points and partitions marked by program behind special. In next phase program alone classifies gained data and designating without doctor diagnose that doctor can evaluate and in case agreeable it sign and place for true diagnose patient. This program is also fit for data reading from bigger of the number of hours as far as days. It is concerned primarily Holter ECG monitoring.
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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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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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Design of algorithms for neural networks controlling a network element
Stískal, Břetislav ; Kacálek, Jan (referee) ; Škorpil, Vladislav (advisor)
This diploma thesis is devided into theoretic and practice parts. Theoretic part contains basic information about history and development of Artificial Neural Networks (ANN) from last century till present. Prove of the theoretic section is discussed in the practice part, for example learning, training each types of topology of artificial neural networks on some specifics works. Simulation of this networks and then describing results. Aim of thesis is simulation of the active networks element controlling by artificial neural networks. It means learning, training and simulation of designed neural network. This section contains algorithm of ports switching by address with Hopfield's networks, which used solution of typical Trade Salesman Problem (TSP). Next point is to sketch problems with optimalization and their solutions. Hopfield's topology is compared with Recurrent topology of neural networks (Elman's and Layer Recurrent's topology) their main differents, their advantages and disadvantages and supposed their solution of optimalization in controlling of network's switch. From thesis experience is introduced solution with controll function of ANN in active networks elements in the future.
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Application of neural networks in telecommunications
Šulák, Michal ; Koula, Ivan (referee) ; Kacálek, Jan (advisor)
This Master’s Thesis consists of description of current routing protocols and routers, basic principles of neural networks and their interpretation in connection with the use for routing in data networks and telecommunications networks. In the thesis I focused on neural networks, which use energetic functions to find solution stabled states and their use for data routing. I produced the application software to test and find suitable variables for each function. This application counts the shortest path and is able to change variables to reach the best solution of stabled state of neural network. These solutions are compared with other functions that are usually used in nowadays systems for data network routing.
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Utilization of inverse reliability analysis tools for probability based design of selected structural parameters
Lipowczan, Martin ; Novák, Drahomír (referee) ; Lehký, David (advisor)
This bachelor thesis deals with the application of methodology and tools of inverse analysis in regards to probabilistic design of selected design parameters of structure. The first step was to get familiar with the probabilistic design and analysis, then understanding of the inverse analysis methodology itself which is based on artificial neural networks. After researching the topic we could get to the actual issue. To put the theory in practice easier examples were used at first. These were mathematical functions and one practical-based example, whereas the results were known in advance. This simplified a process of checking achieved values. Using software tools and especially DLNNET software allowed us to take on practical exercises. Used exercises are chosen from earlier undergraduate studies at the Faculty of Civil Engineering, Brno. The first of these was a design of reinforced concrete slab, where desired parameters were slab’s height and area of reinforcement. The second one was a design of a diagonal truss screw connection, aimed to size the screw diameter and its quantity.
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Modern trends in the area of computer physics
SURYNEK, Radek
The theme of the thesis is to make a list few fundamental modern methods which can be used in computerized physics. The thesis describes parallel computing, neural networks,genetic algorithms, fuzzy logic. Every chapter include theoretical description, simplified mathematical expression, proposals of technical solution. Applications are briefly mentioned here too. The printed matter is completed with a few simple examples. The closing part of the thesis acquired information about these methods and outlines their future development.
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