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Iterative method of neural elements synthesis with generalized threshold activation function

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Języki publikacji
EN
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EN
Present work considers the neural elements (NE) with generalized threshold activation function and represents iterative method of their synthesis. Algorithm of vectors finding for structures of the neural elements with generalized threshold activation function was developed, and the sufficient condition of Boolean function unreliazability on such neural elements was discovered.
Twórcy
autor
  • Uzhhorod National University
autor
  • Lviv Polytechnic National University
autor
  • Uzhhorod National University
autor
  • Lviv Polytechnic National University
Bibliografia
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  • 6. Geche F., Kotsovsky V., Batyuk A., Geche S. and Vashkeba M. 2015. Synthesis of Time Series Forecasting Scheme Based on Forecasting Models System. Lviv: Proceedings of the 11th International Conference «ICTERI 2015», 121-136.
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  • 10. Gunasundari S. and Baskar S. 2009. Application of Artificial Neural Network in identification of lung diseases. Nature & Biologically Inspired Computing (IEEE). 1441–1444.
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  • 18. Bodyanskiy Y. V., Kucherenko V. Y., Kucherenko Y. I., Mykhalyov O. I. and Filatov V. A. 2008. Hybrid neuro- phase models and multiagent technologies in complicated systems. Dnipropetrovsk: System technologies. 403. (in Ukrainian).
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c670128f-ad35-40ad-9c32-cd71f774c87d
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