Research output: Contribution to journalConference articlepeer-review


Stochastic bounds are derived for one-dimensional diffusions (and somewhat more general random processes) by dominating one process pathwise by a convex combination of other processes. The method permits comparison of diffusions with different diffusion coefficients. One interpretation of the bounds is that an optimal control is identified for certain diffusions with controlled drift and diffusion coefficients, when the reward function is convex. An example is given to show how the bounds and the Lyapunov function technique can be applied to yield bounds for multidimensional diffusions.

Original languageEnglish (US)
Pages (from-to)1490-1491
Number of pages2
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 1984

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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