Biased Boltzmann samplers and generation of extended linear languages with shuffle

Biased Boltzmann samplers and generation of extended linear languages with shuffle

This paper is devoted to the construction of Boltzmann samplers according to various distributions, and uses stochastic bias on the parameter of a Boltzmann sampler, to produce a sampler with a different distribution for the size of the output. As a significant application, we produce Boltzmann samp...

Full description

Bibliographic Details
Main Authors: Alexis Darrasse, Konstantinos Panagiotou, Olivier Roussel, Michele Soria
Format: Article
Language:English
Published: Discrete Mathematics & Theoretical Computer Science 2012-01-01
Series:Discrete Mathematics & Theoretical Computer Science
Subjects:
boltzmann samplers
biased distributions
shuffle operator
combinatorial specifications
generating functions
random sampling
[info.info-ds] computer science [cs]/data structures and algorithms [cs.ds]
[info.info-dm] computer science [cs]/discrete mathematics [cs.dm]
[math.math-co] mathematics [math]/combinatorics [math.co]
[info.info-cg] computer science [cs]/computational geometry [cs.cg]
Online Access:https://dmtcs.episciences.org/2989/pdf

Internet

https://dmtcs.episciences.org/2989/pdf

Similar Items