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Almost sure convergence of randomly truncated stochastic algorithms under verifiable conditions

Probability 2009-06-29 v1
Authors: Jérôme Lelong
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Abstract

We study the almost sure convergence of randomly truncated stochastic algorithms. We present a new convergence theorem which extends the already known results by making vanish the classical condition on the noise terms. The aim of this work is to prove an almost sure convergence result of randomly truncated stochastic algorithms under easily verifiable conditions

Keywords

almost sure convergence randomly truncated stochastic algorithms convergence theorem noise condition

Cite

@article{arxiv.0706.0841,
  title  = {Almost sure convergence of randomly truncated stochastic algorithms under verifiable conditions},
  author = {Jérôme Lelong},
  journal= {arXiv preprint arXiv:0706.0841},
  year   = {2009}
}

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