Accuracy Estimates for Surrogate Solutions of Integral Equations by Neural Networks

Authors: Věra Kůrková
Publication year: 2012
Publication type: Konferenční příspěvek (mezinárodní konf.)
Periodical: SOFSEM 2012: Theory and Practice of Computer Science
Projects: Analysis of Intelligent Computational Distributed Systems
Bibliographic citation: KŮRKOVÁ, Věra. Accuracy Estimates for Surrogate Solutions of Integral Equations by Neural Networks. In: BIELIKOVÁ, M., FRIEDRICH, G., GOTTLOB, G., KATZENBEISSER, S., ŠPÁNEK, R., TURÁN, G., eds. SOFSEM 2012: Theory and Practice of Computer Science. Vol. 2. Prague: Institute of Computer Science AS CR, 2012, S. 95-102. ISBN 978-80-87136-13-3.
ID: 374354

Abstract

Surrogate solutions of integral equations by neural networks are investigated theoretically. Upper bounds on speed of convergence of approximate solutions computable by neural networks with increasing model complexity to exact solutions described by Fredholm theorem are derived.