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Fuzzy map models for mobile robots
Machek, Ondřej ; Burian, František (referee) ; Jura, Pavel (advisor)
This master thesis present a method for building topological maps for mobile robot navigation using neural network and neural fuzzy network. The master thesis concentrates on classification method. Neural fuzzy network is compared with two neural networks. It was also designed control algorithm exploration environment for autonomous mobile robot. This will rereduce the time to build the map. I developed simulation program in Matlab, which simulate move mobile robot in unknown environment.
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Travelling Salesman Problem
Kolář, Adam ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
The aim of this bachelor's thesis is to design a testing environment for the traveling salesman problem and compare the effectiveness of different approaches to the solution. The first part discussed the possibility of genetic algorithms, depending on the setting of a crossover, mutations and population size. In the second part, there is the same problem using two types of neural networks. The representative of the self-learning net was chosen Kohonen neural network. Hopfield neural network represents a method of minimizing the energy function with fixed coefficients. At both neural networks, there were described possible advantages and disadvantages. In the end, all the findings were interpreted in a global context.
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Simulation Design in Communication System Training
Takács, Endre ; Krkoš, Radko (referee) ; Škorpil, Vladislav (advisor)
The aim of this work was to analyze the problematics of modern communication systems focusing on the converged network and their elements and to propose a laboratory work. The theoretical part of the work is extensive. It deals with the network architecture OSI, which forms the basic of modern communication networks. It describes also the active network elements and their characteristics, advantages and disadvantages. The theoretical part deals in a chapter with the neuron networks, which describes the basic artificial neuron of a network, which can be used for the controlling of network elements. These networks are Hopfield network and Kohonen network. The practical part deals with the proposing of the laboratory work into the education, which is focused on the Hopfield network and the functioning of classifier switches. The work is made in Matlab.
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Network Element with Advanced Control
Zedníček, Petr ; Kacálek, Jan (referee) ; Škorpil, Vladislav (advisor)
The diploma thesis deal with finding and testing neural networks, whose characteristics and parameters suitable for the active management of network element. Solves optimization task priority switching of data units from input to output. Work is focused largely on the use of Hopfield and Kohonen networks and their optimization. Result of this work are two models. The first theory is solved in Matlab, where each comparing the theoretical results of neural networks. The second model is a realistic model of the active element designed in Simulink
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Simulation Design in Communication System Training
Takács, Endre ; Krkoš, Radko (referee) ; Škorpil, Vladislav (advisor)
The aim of this work was to analyze the problematics of modern communication systems focusing on the converged network and their elements and to propose a laboratory work. The theoretical part of the work is extensive. It deals with the network architecture OSI, which forms the basic of modern communication networks. It describes also the active network elements and their characteristics, advantages and disadvantages. The theoretical part deals in a chapter with the neuron networks, which describes the basic artificial neuron of a network, which can be used for the controlling of network elements. These networks are Hopfield network and Kohonen network. The practical part deals with the proposing of the laboratory work into the education, which is focused on the Hopfield network and the functioning of classifier switches. The work is made in Matlab.
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|
Travelling Salesman Problem
Kolář, Adam ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
The aim of this bachelor's thesis is to design a testing environment for the traveling salesman problem and compare the effectiveness of different approaches to the solution. The first part discussed the possibility of genetic algorithms, depending on the setting of a crossover, mutations and population size. In the second part, there is the same problem using two types of neural networks. The representative of the self-learning net was chosen Kohonen neural network. Hopfield neural network represents a method of minimizing the energy function with fixed coefficients. At both neural networks, there were described possible advantages and disadvantages. In the end, all the findings were interpreted in a global context.
|
|
|
Fuzzy map models for mobile robots
Machek, Ondřej ; Burian, František (referee) ; Jura, Pavel (advisor)
This master thesis present a method for building topological maps for mobile robot navigation using neural network and neural fuzzy network. The master thesis concentrates on classification method. Neural fuzzy network is compared with two neural networks. It was also designed control algorithm exploration environment for autonomous mobile robot. This will rereduce the time to build the map. I developed simulation program in Matlab, which simulate move mobile robot in unknown environment.
|
|
|
Network Element with Advanced Control
Zedníček, Petr ; Kacálek, Jan (referee) ; Škorpil, Vladislav (advisor)
The diploma thesis deal with finding and testing neural networks, whose characteristics and parameters suitable for the active management of network element. Solves optimization task priority switching of data units from input to output. Work is focused largely on the use of Hopfield and Kohonen networks and their optimization. Result of this work are two models. The first theory is solved in Matlab, where each comparing the theoretical results of neural networks. The second model is a realistic model of the active element designed in Simulink
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