An application of proof mining to nonlinear iterations
classification
🧮 math.LO
math.FA
keywords
convexminingproofapplicationapplyassociatedasymptoticclass
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In this paper we apply methods of proof mining to obtain a highly uniform effective rate of asymptotic regularity for the Ishikawa iteration associated to nonexpansive self-mappings of convex subsets of a class of uniformly convex geodesic spaces. Moreover, we show that these results are guaranteed by a combination of logical metatheorems for classical and semi-intuitionistic systems.
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