On the Horton-Strahler Number  for Combinatorial Tries

Markus E. Nebel

Displaying similar documents to “On the Horton-Strahler Number for Combinatorial Tries”

A Compositional Approach to Synchronize Two Dimensional Networks of Processors

Salvatore La Torre, Margherita Napoli, Mimmo Parente (2010)

RAIRO - Theoretical Informatics and Applications

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The problem of synchronizing a network of identical processors that work synchronously at discrete steps is studied. Processors are arranged as an array of rows and columns and can exchange each other only one bit of information. We give algorithms which synchronize square arrays of ( × ) processors and give some general constructions to synchronize arrays of ( × ) processors. Algorithms are given to synchronize in time , $n ⌈ log n ⌉$ , $n ⌈ \sqrt{n} ⌉$ and 2 a square array of ( × ) processors. Our...

On the power of randomization for job shop scheduling with -units length tasks

Tobias Mömke (2008)

RAIRO - Theoretical Informatics and Applications

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In the job shop scheduling problem -- , there are machines and each machine has an integer processing time of at most time units. Each job consists of a permutation of tasks corresponding to all machines and thus all jobs have an identical dilation . The contribution of this paper are the following results; (i) for $d = o (\sqrt{D})$ jobs and every fixed , the makespan of an optimal schedule is at most , which extends the result of [3] for ; (ii) a randomized on-line approximation...

Asymptotic behavior of the hitting time, overshoot and undershoot for some Lévy processes

Bernard Roynette, Pierre Vallois, Agnès Volpi (2007)

ESAIM: Probability and Statistics

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Let () be a Lévy process started at , with Lévy measure . We consider the first passage time of () to level , and the overshoot and the undershoot. We first prove that the Laplace transform of the random triple () satisfies some kind of integral equation. Second, assuming that admits exponential moments, we show that $(\tilde{T_{x}}, K_{x}, L_{x})$ converges in distribution as → ∞, where $\tilde{T_{x}}$ denotes a suitable renormalization of . 