Ways of Selecting Internal Patterns in Multilayer Perceptron Network

• Autorzy: Kolibabka M. , Cader A. , Siwocha A. , Krupski M.
• Języki publikacji: EN

Abstrakty

EN

Creating and later learning one-way neural networks depends on many factors. Selecting many of them has estimated and experimental character. The suggested method is the Allows weakness of the influence of the not optimal choice of the net structure, also speed and momentum values are less influential in classic Back then Propagation Method. There are few modes of choosing elements to use in Followed algorithm.

Słowa kluczowe

EN

neural networks; artificial intelligence; back propagation

• Wydawca: Społeczna Akademia Nauk w Łodzi
• Czasopismo: Journal of Applied Computer Science Methods
• Rocznik: 2012
• Tom: Vol. 4 No. 1
• Strony: 63--73
• Opis fizyczny: Bibliogr. 9 poz., tab.

Twórcy

autor

Kolibabka M.

• Information Technology Institute, University of Social Science, Lodz, Poland

autor

Cader A.

• Information Technology Institute, University of Social Science, Lodz, Poland

autor

Siwocha A.

• Information Technology Institute, University of Social Science, Lodz, Poland

autor

Krupski M.

• Department of Computer Science in Economics Institute of Applied Economics and Informatics Faculty of Economics and Sociology University of Lodz, Poland

Bibliografia

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• 2. Cybenko G., 1989, Approximation by Superpositions of a Sigmoidal Function, Mathematics of Control, Signals, and Systems, Vol. 2 ,pp. 303–314.
• 3. Rutkowska D., Piliński M., Rutkowski L., 1997, Sieci neuronowe, algorytmy genetyczne i systemy rozmyte, Wydawnictwo Naukowe PWN, Warszawa.
• 4. Rumelhart D., Hinton G., Williams R., 1986, Learning Internal Representations by Error Propagation. Parallel Distributed Processing, Vol.1, pp.318–362.
• 5. Hornik K., Stinchcombe M., White H., 1989, Multilayer feedforward networks are universal approximators. Neural Networks, 2, pp. 359–366.
• 6. Rutkowski L., 2005, Metody i techniki sztucznej inteligencji, Wydawnictwo Naukowe PWN, Warszawa.
• 7. Kolibabka M., Cader A., 2006, Metoda wymuszania wewnętrznych wzorców w jednokierunkowej sieci klasyfikującej, Automatyka, 10, 3, pp. 497–502.
• 8. Haykin S., 1994, Neural networks: A Comprehensive Foundation, Macmikkan College Publishing Company, New York.
• 9. Bishop Ch.M., 1995, Neural Networks for Pattern Recognition, Oxford University Press, Oxford, New York.