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FSI-RNFAcad. year: 2014/2015
The course provides students with the introduction to the most commonly used paradigms of neural networks. Further, it shows technically oriented applications of neural networks and their practical use. The theory part is focused on neural dynamics - mainly it's activation, signals and activation models, synapse dynamics - both supervised and unsupervised learning (competitive learning, back-propagation); network architectures. Furthermore, the neural and fuzzy representation of structured knowledge is compared and used for controllers design.
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Specification of controlled education, way of implementation and compensation for absences
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branch M-MET , 2 year of study, winter semester, compulsory
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