Open AccessThe Essential Order of (L_p,p<1) Approximation Using Regular Neural Networks
Author(s) -
Eman Samir Bhaya,
Omar A. Al-sammak
Publication year - 2017
Publication title -
journal of university of babylon for pure and applied sciences
Language(s) - English
Resource type - Journals
eISSN - 2312-8135
pISSN - 1992-0652
DOI - 10.29196/jub.v26i1.356
Subject(s) - multivariate statistics , artificial neural network , mathematics , order (exchange) , function (biology) , degree (music) , computer science , artificial intelligence , statistics , biology , physics , evolutionary biology , economics , finance , acoustics
This paper is concerning with essential degree of approximation using regular neural networks and how a multivariate function in spaces for can be approximated using a forward regular neural network. So, we can have the essential approximation ability of a multivariate function in spaces for using regular FFN.
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