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Critical Path Statistics of Max-Plus Linear Systems with Gaussian Noise

Published online by Cambridge University Press:  30 January 2018

James Hook*
Affiliation:
University of Manchester
*
Postal address: Alan Turing Building, University of Manchester, Oxford Road, Manchester M13 9PL, UK. Email address: james.hook@manchester.ac.uk
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Abstract

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The critical paths of a max-plus linear system with noise are random variables. In this paper we introduce the edge criticalities which measure how often the critical paths traverse each edge in the precedence graph. We also present the parallel path approximation, a novel method for approximating these new statistics as well as the previously studied max-plus exponent. We show that, for low amplitude noise, the critical paths spend most of their time traversing the deterministic maximally weighted cycle and that, as the noise amplitude is increased, the critical paths become more random and their distribution over the edges in the precedence graph approaches a highly uniform measure of maximal entropy.

Type
Research Article
Copyright
© Applied Probability Trust 

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