ESTIMATING GRAPH PARAMETERS WITH RANDOM WALKS

In order to prove Theorem 3, we compute the Laplace transform of the volume of truncated hulls centered at the root vertex of the uipq , and derive an upper bound on the

The graph of triangulations of the sphere in which two triangulations are related if one can pass from one to the other by flipping an edge has already been studied in the

when the distances are renormalized, T n (∞) to a continuum random metric space called the Brownian map [Le Gall], if we don’t renormalize the distances and look at a neighbourhood

KITADA, Time decay of the high energy part of the solutionfor a Schrödinger equation, preprint University of Tokyo, 1982. [9]

This work is a continuation of the paper [6] in which the authors studied the exponential decreasing rate of the probability that a random walk (with some exponential moments) stays

Finally, in Section 5 we prove the non-exponential decay of the non-exit probability for random walks with drift in the cone (a refinement of a theorem of [16]), which is needed

It means that the algorithm must calculate as fast as the sampling frequency for that condition and provide an easy estimation of calculation cycles for different counted

In this paper, we present a real-time implementation of a Self-Mixing (SM) interferometric laser diode (LD) based vibration sensor coupled with an embedded MEMS