Comparison of Libraries of Artificial Neural Networks

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