Convergence in Orlicz spaces by means of the multivariate max-product neural network operators of the Kantorovich type and applications-Reference-Cited by-同舟云学术

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Convergence in Orlicz spaces by means of the multivariate max-product neural network operators of the Kantorovich type and applications

Published:2019-01-12 Issue:9 Volume:31 Page:5069-5078
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Costarelli Danilo^ORCID,Sambucini Anna Rita^ORCID,Vinti Gianluca^ORCID

Funder

Gruppo Nazionale per l’Analisi Matematica, la Probabilità e le loro Applicazioni

Department of Mathematics and Computer Science of the University of Perugia

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/article/10.1007/s00521-018-03998-6/fulltext.html

Reference52 articles.

1. Adler A, Guardo R (1994) A neural network image reconstruction technique for electrical impedance tomography. IEEE Trans Med Imaging 13(4):594–600

2. Angeloni L, Costarelli D, Vinti G (2018) A characterization of the convergence in variation for the generalized sampling series. Annales Academiae Scientiarum Fennicae Mathematica 43:755–767

3. Angeloni L, Vinti G (2009) Convergence and rate of approximation for linear integral operators in $$BV^\varphi $$ B V φ -spaces in multidimensional setting. J Math Anal Appl 349:317–334

4. Angeloni L, Vinti G (2010) Approximation with respect to Goffman–Serrin variation by means of non-convolution type integral operators. Numer Funct Anal Optim 31:519–548

5. Angeloni L, Vinti G (2014) Convergence and rate of approximation in BV $$\varphi ({\mathbb{R}}^N_+)$$ φ ( R + N ) for a class of Mellin integral operators. Atti Accad Naz Lincei Rend Lincei Mat Appl 25:217–232

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