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Radial Basis Function Neural Network
Nevoral, Leoš ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
The thesis focuses on explaining the field of RBF neural networks, specifically RCE networks, through a demo application. The demo application primarily visualizes the network learning process, as well as the state of the neural network and different shapes of basis functions. Additionally, the utilization of EBF neural networks is explored. Conventional approaches to EBF networks are compared and tested against new design of OEBF network. Which is based on deriving the elliptical areas from euclidean distance from both focal points of ellipse. The new design shows no signs of improving the properties of these networks and rather produces results almost identical to those of the classic RCE network, which are, however, several percentage points less accurate. Finally, methods for improving this solution in future are proposed.
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Neural Networks Application
Macůrek, Miloslav ; Jindra, Petr (referee) ; Šťastný, Jiří (advisor)
This Bechelor’s thesis will cover the theme of neural networks, their history, characteristics, basic typology of neural networks and learning algorithms and analysis of their applications demonstrated in simple examples created in MATLAB software.
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Prediction of Raining from Meteoradar
Vlček, Michael ; Pešán, Jan (referee) ; Szőke, Igor (advisor)
This thesis deals with rain prediction using information from meteoradar images and some other relevant factors through the computational model of a neural network. It focuses on exploring different prediction possibilities using this model and defining the most successful model configuration to fulfill the chosen task.
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Neural Networks Application
Macůrek, Miloslav ; Jindra, Petr (referee) ; Šťastný, Jiří (advisor)
This Bechelor’s thesis will cover the theme of neural networks, their history, characteristics, basic typology of neural networks and learning algorithms and analysis of their applications demonstrated in simple examples created in MATLAB software.
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Prediction of Raining from Meteoradar
Vlček, Michael ; Pešán, Jan (referee) ; Szőke, Igor (advisor)
This thesis deals with rain prediction using information from meteoradar images and some other relevant factors through the computational model of a neural network. It focuses on exploring different prediction possibilities using this model and defining the most successful model configuration to fulfill the chosen task.
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