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Comparison of Libraries of Artificial Neural Networks
Dohnal, Zdeněk ; Zbořil, František (referee) ; Dalecký, Štěpán (advisor)
This thesis is about comparison of libraries of artificial neural networks. Basic theory of neuron, neural networks and their learning algorithms are explained here. Multilayer perceptron, Self organizing map and Hopfield net are chosen for experiments. Criteria of comparison such as licence, community or last actualization are designed. Approximation of function, association and clustering are chosen as task for experiments. After that, there is implementation of applications using chosen libraries. At the end, result of comparison and experiment are evaluated.
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Neural Network Library and Editor
Rouček, Martin ; Ježek, Pavel (advisor) ; Pešková, Klára (referee)
Neural network models are more often used in desktop applications given the increasing speed of computers. A very widespread platform for writing desktop applicatons is .NET Framework. Nevertheless, there is no neural networks library for the .NET Framework platform with a simple API and the possibility to work with library objects in a graphical interface. The author decided to create such a library. The main part of the thesis is a neural networks library GNNL that is initially limited to implementing two frequently used neural networks models which are a multilayer perceptron and self- organizing map together with learning algorithms of backpropagation and competitive learning. Graphical support of the library GNNL consists of a library GNNLV and neural network editor. The Library GNNLV contains the controls that allow working with GNNL library objects and a programmer can use them in his or hers application. The Neural network editor enables the programmer to create a neural network in a graphical interface, train it, analyze it, save it, and later use it in different applications. Text of the thesis focuses on analyzing and describing the implementation of the library with its graphical support. A major component of the text is a summary of neural networks theory for laics or programmers using library...
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Comparison of Libraries of Artificial Neural Networks
Dohnal, Zdeněk ; Zbořil, František (referee) ; Dalecký, Štěpán (advisor)
This thesis is about comparison of libraries of artificial neural networks. Basic theory of neuron, neural networks and their learning algorithms are explained here. Multilayer perceptron, Self organizing map and Hopfield net are chosen for experiments. Criteria of comparison such as licence, community or last actualization are designed. Approximation of function, association and clustering are chosen as task for experiments. After that, there is implementation of applications using chosen libraries. At the end, result of comparison and experiment are evaluated.
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