P069 Hybridní systémy strojového učení

Faculty of Informatics
Spring 1997
Extent and Intensity
2/1. 3 credit(s). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
Teacher(s)
doc. Ing. Jan Žižka, CSc. (lecturer)
Guaranteed by
Contact Person: doc. Ing. Jan Žižka, CSc.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Syllabus
  • Hybrid neural networks, a fuzzy perceptron, an AND/OR fuzzy neuron with t-norms and s-norms. Fuzzy neural networks.
  • NEFCON and ANFIS architectures of hybrid neural networks. Neuro-fuzzy classifiers. Optimization of fuzzy rules by neural networks and genetic algorithms.
  • Genetic algorithms and simulated annealing combined with neural networks, optimization of neural networks. Nonlinear dynamical systems, chaos, strange attractors. Recurrent networks, Hopfield networks.
  • Applications of decision trees to the setup of neural network weights.
  • Fuzzy-genetic modelling. Genetic programming.
  • Application examples.
Language of instruction
Czech
The course is also listed under the following terms Spring 1998, Spring 2001, Spring 2002.
  • Enrolment Statistics (Spring 1997, recent)
  • Permalink: https://is.muni.cz/course/fi/spring1997/P069