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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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Approximation Capabilities of a Neural Network

Gammelli, Elin January 2024 (has links)
This essay proves the Universal Approximation Theorem for discriminatory activation functions, in particular continuous sigmoidal functions, over compact spaces. In other words, a neural network with a discriminatory activation function can approximate any continuous function over a compact space. The theorem guarantees the effectivity of neural networks. / Denna uppsats bevisar Universala Approximations Satsen för diskriminerande funktioner, särskillt kontinuerliga sigmoidala funktioner, över kompakta rum. Med andra ord, ett neuralt nätverk med en discriminerande aktiveringsfunktion kan approximera alla kontinguerliga functioner över kompakta rum. Satsen garanterar effektivitet av neurala nätverk.
Neural network
cybenko
artifical intelligence
integration theory
Mathematical Analysis
Matematisk analys
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Mathematics
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