FI:P021 Neural Networks - Course Information
P021 Neural Networks
Faculty of InformaticsAutumn 1999
- Extent and Intensity
- 2/2. 4 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
- Teacher(s)
- doc. RNDr. Jiří Šíma, DrSc. (lecturer), prof. RNDr. Mojmír Křetínský, CSc. (deputy)
- Guaranteed by
- prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science – Faculty of Informatics
Contact Person: prof. RNDr. Mojmír Křetínský, CSc. - Prerequisites
- M001 Calculus II && M004 Linear Algebra II
Prerequisites: M001 Calculus II and M004 Linear Algebra and Geometry II - Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
- fields of study / plans the course is directly associated with
- Informatics (programme FI, B-IN)
- Informatics (programme FI, M-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
- Information Technology (programme FI, B-IN)
- 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.
- Literature
- BEALE, R. and T. JACKSON. Neural Computing :An introduction. Bristol: Institute of Physics Publishing, 1994, xv, 240 s. ISBN 0-85274-262-2. info
- HAYKIN, Simon S. Neural Networks : a comprehensive foundation. New York: Macmillan College Publishing Company, 1994, xix, 696. ISBN 0023527617. info
- Neural networks - theory and architecture. Edited by Arun Holden - Vitaly I. Kryukov. Manchester: Manchester University Press, 1990, 236 s. ISBN 0-7190-3279-2. info
- HECHT-NIELSEN, Robert. Neurocomputing. Reading, Mass.: Addison-Wesley Publishing Company, 1990, xiii, 433. ISBN 0-201-09355-3. info
- Sofsem '88 : sborník referátů : Zotavovna ROH Petr Bezruč, Malenovice, Beskydy 27.11.-9.12.1988. Brno: Ústav výpočetní techniky UJEP Brno, 1988, 363 s. info
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
The course is taught: every other week.
- Enrolment Statistics (Autumn 1999, recent)
- Permalink: https://is.muni.cz/course/fi/autumn1999/P021