Course details

Soft Computing

SFC Acad. year 2010/2011 Winter semester 5 credits

Current academic year

Guarantor

Zbořil František, doc. Ing., CSc. (DITS)

Language of instruction

Czech

Completion

Examination

Time span

  • 26 hrs lectures
  • 26 hrs projects

Department

Department of Intelligent Systems (UITS)

Study literature

    1. Mehrotra, K., Mohan, C. K., Ranka, S.: Elements of Artificial Neural Networks, The MIT Press, 1997, ISBN 0-262-13328-8
    2. Munakata, T.: Fundamentals of the New Artificial Intelligence, Springer-Verlag New York, Inc., 2008. ISBN 978-1-84628-838-8
    3. Russel, S., Norvig, P.: Artificial Intelligence, Prentice-Hall, Inc., 1995, ISBN 0-13-360124-2, second edition 2003, ISBN 0-13-080302-2, third edition 2010, ISBN 0-13-604259-7

Fundamental literature

Syllabus of lectures

  1. Introduction, Soft Computing concept explanation. Importance of tolerance of imprecision and uncertainty.
  2. Biological and artificial neuron, neural networks. Adaline, Perceptron. Madaline and BP (Back Propagation) neural networks.
  3. Adaptive feedforward multilayer networks.
  4. RBF and RCE neural networks. Topologic organized neural networks, competitive learning, Kohonen maps.
  5. CPN , LVQ, ART, Neocognitron neural networks
  6. Neural networks as associative memories (Hopfield, BAM, SDM).
  7. Solving optimization problems using neural networks. Stochastic neural networks, Boltzmann machine.
  8. Fuzzy sets, fuzzy logic and fuzzy inference.
  9. Genetic algorithms.
  10. Probabilistic reasoning.
  11. Rough sets.
  12. Chaos.
  13. Hybrid approaches (neural networks, fuzzy logic, genetic algorithms sets).

Course inclusion in study plans

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