P021 Neuronové sítě I

Faculty of Informatics
Autumn 1996
Extent and Intensity
2/0. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Jiří Hořejš, CSc. (lecturer)
Guaranteed by
Contact Person: doc. RNDr. Jiří Hořejš, CSc.
Prerequisites
Prerequisites: M001 Calculus II and M004 Linear Algebra and Geometry II
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
  • Introduction to Neural Networks. History of neurocomputing; neurophysiological motivations; mathematical model of neural network: formal neuron, organizational, active, and adaptive dynamics; position of neural networks in computer science: comparison with von Neumann computer architecture, applications, implementations, neurocomputers.
  • Classical Models of Neural Networks. Perceptron: convergence; multi-layered network and backpropagation strategy: choice of topology and generalization; MADALINE: Widrow learning rule.
  • Associative Neural Networks. Linear associative network: Hebb law and pseudohebbian adaptation; Hopfield network: energy, capacity; continuous Hopfield network: traveling salesman problem; Boltzmann machine: simulated annealing, equilibrium.
  • Self-Organization. Kohonen network: unsupervised learning; Kohonen maps; counterpropagation: Grossberg learning rule.
  • Seminar: Software implementation of particular neural network models and their simple applications.
Language of instruction
Czech
The course is also listed under the following terms Autumn 1995, Autumn 1998, Autumn 1999, Spring 2001, Autumn 2001.
  • Enrolment Statistics (Autumn 1996, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn1996/P021