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Speed of learning multilayer network
Maceček, Aleš ; Zámečník, Dušan (referee) ; Jirsík, Václav (advisor)
Theoretical study about neural networks, especially their types of topologies and networks learning. Special attention is attended to multilayer neural network with learning backpropagation. Introduced learning algorithm backpropagation of simple networks in conjunction with descriptions of parameters affecting network learning also methods to exaluation quality of network learning. Definition moment invariants to rotation, translation and scaling. Optimalization parameters of neural networks to find the network which has the fastest learning and also the networks with the best value of recognition patterns of letters from testing set.
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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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Speed of learning multilayer network
Maceček, Aleš ; Zámečník, Dušan (referee) ; Jirsík, Václav (advisor)
Theoretical study about neural networks, especially their types of topologies and networks learning. Special attention is attended to multilayer neural network with learning backpropagation. Introduced learning algorithm backpropagation of simple networks in conjunction with descriptions of parameters affecting network learning also methods to exaluation quality of network learning. Definition moment invariants to rotation, translation and scaling. Optimalization parameters of neural networks to find the network which has the fastest learning and also the networks with the best value of recognition patterns of letters from testing set.
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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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