Multivariate Jackson-type inequality for a new type neural network approximation

In this paper, we introduce a new type neural networks by superpositions of a sigmoidal function and study its approximation capability. We investigate the multivariate quantitative constructive approximation of real continuous multivariate functions on a cube by such type neural networks. This appr...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Applied mathematical modelling 2014-12, Vol.38 (24), p.6031-6037
Hauptverfasser:	Lin, Shaobo, Rong, Yuanhua, Xu, Zongben
Format:	Artikel
Sprache:	eng
Schlagworte:	Approximation Error estimate Inequalities Jackson-type inequality Mathematical analysis Mathematical models Networks Neural networks Sigmoidal function Smoothness Training
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!