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  • 标题:Algorithmic randomness for Doob's martingale convergence theorem in continuous time
  • 本地全文:下载
  • 作者:Bjørn Kjos-Hanssen ; Paul Kim Long Nguyen ; Jason Rute
  • 期刊名称:Logical Methods in Computer Science
  • 印刷版ISSN:1860-5974
  • 电子版ISSN:1860-5974
  • 出版年度:2014
  • 卷号:10
  • 期号:4
  • 页码:1
  • DOI:10.2168/LMCS-10(4:12)2014
  • 出版社:Technical University of Braunschweig
  • 摘要:We study Doob's martingale convergence theorem for computable continuous time martingales on Brownian motion, in the context of algorithmic randomness. A characterization of the class of sample points for which the theorem holds is given. Such points are given the name of Doob random points. It is shown that a point is Doob random if its tail is computably random in a certain sense. Moreover, Doob randomness is strictly weaker than computable randomness and is incomparable with Schnorr randomness.
  • 其他关键词:Doob’s martingale convergence theorem, algorithmic randomness, computability theory, Schnorr randomness, computable randomness, Brownian motion.
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