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Neural Networks
Abbreviation: Load: 30(L) + 0(E) + 0(LE) + 0(CE)
Lecturers in charge: Prof. dr. sc. Sven Lončarić
Lecturers:
Course description: The course provides knowledge in theory and applications of artificial neural networks and genetic algorithms. Biological neural networks. Artificial neural networks. Definition. Neuron models. Activation function. Network topologies. Perceptron. Learning laws. Associative networks. Linear associator. Recursive associative networks. Hopfield network. Energy function. Multi-layer networks. Delta rule for error back-propagation. Kohonen self-organizing network. K-means clustering algorithm. Boltzmann machine. Simulated annealing. Genetic algorithms. Software for simulation of neural networks. Applications in pattern recognition and signal and image analysis.
Lecture languages: - - -
Compulsory literature:
1. Predavanja iz neuronskih mreža S. Lončarić Autor 2005
Recommended literature:
2. Neural Networks, 2nd Ed. S. Haykin Prentice Hall 1998
3. An Introduction to Neural Networks J. A. Anderson MIT Press 1995
Legend
L - Lectures
E - Exercises
LE - Laboratory exercises
CE - Project laboratory
* - Not graded
Copyright (c) 2006. Ministarstva znanosti, obrazovanja i športa. Sva prava zadržana.
Programska podrška (c) 2006. Fakultet elektrotehnike i računarstva.
Oblikovanje(c) 2006. Listopad Web Studio.
Posljednja izmjena 2011-07-03