On a comparative analysis of the solutions of the kinetic neutron diffusion equation by the Hankel transform formalism and the spectral method

Fernandes, J. C. L.; Vilhena, Marco T.; Bodmann, B. E. J.

doi:10.1016/j.pnucene.2013.05.009

Cited by 13 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Arteaga and Marrero [3], and Baddour [4] developed Hankel convolution theory. Recently, Hankel convolution linear operators have attracted many interests since these operators have many applications such as solving optic problems [5], radiation, diffraction, and field projection [6], and neutron transportation equation [7].…”

Section: Introductionmentioning

confidence: 99%

Solving Universal Approximation Problem by Hankel Approximate Identity Neural Networks in Function Spaces

Fard

2016

Proceedings of the Fourth International Conference on Information Science and Cloud Computing — PoS(ISCC2015)

View full text Add to dashboard Cite

Artificial neural networks has been effectively applied to numerous applications because of their universal approximation property. This work is grounded on two frameworks. Firstly, it is concerned with solving universal approximation problem by a class of neural networks based on Hankel approximate identity which is embedded in the space of continuous functions on real positive numbers. Secondly, this problem solving will be investigated in the Lebesgue spaces on real positive numbers. The methods are constructed on the notions of Hankel convolution linear operators, Hankel approximate identity, and epsilon-net.

show abstract