Neural network modeling of vector multivariable functions in ill-posed approximation problems

DOI10.1134/S1064230713040126zbMath1311.65042MaRDI QIDQ2263827

O. A. Mishulina, I. A. Kruglov

Publication date: 19 March 2015

Published in: Journal of Computer and Systems Sciences International (Search for Journal in Brave)

zbMATH Keywords

numerical examplesill-posed inverse problemneural network solution

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• PRMLT

Cites Work

• Bagging predictors
• Iterative regularization methods for nonlinear ill-posed problems
• Multilayer feedforward networks are universal approximators
• Universal approximation bounds for superpositions of a sigmoidal function
• Weighted bagging: a modification of AdaBoost from the perspective of importance sampling
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