355 research outputs found

    Probabilistic Approach to Fractional Integrals and the Hardy-Littlewood-Sobolev Inequality

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    We give a short summary of Varopoulos' generalised Hardy-Littlewood-Sobolev inequality for self-adjoint C0C_{0} semigroups and give a new probabilistic representation of the classical fractional integral operators on Rn\R^n as projections of martingale transforms. Using this formula we derive a new proof of the classical Hardy-Littlewood-Sobolev inequality based on Burkholder-Gundy and Doob's inequalities for martingales

    Infinitely divisible central probability measures on compact Lie groups---regularity, semigroups and transition kernels

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    We introduce a class of central symmetric infinitely divisible probability measures on compact Lie groups by lifting the characteristic exponent from the real line via the Casimir operator. The class includes Gauss, Laplace and stable-type measures. We find conditions for such a measure to have a smooth density and give examples. The Hunt semigroup and generator of convolution semigroups of measures are represented as pseudo-differential operators. For sufficiently regular convolution semigroups, the transition kernel has a tractable Fourier expansion and the density at the neutral element may be expressed as the trace of the Hunt semigroup. We compute the short time asymptotics of the density at the neutral element for the Cauchy distribution on the dd-torus, on SU(2) and on SO(3), where we find markedly different behaviour than is the case for the usual heat kernel.Comment: Published in at http://dx.doi.org/10.1214/10-AOP604 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Deterministic Rateless Codes for BSC

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    A rateless code encodes a finite length information word into an infinitely long codeword such that longer prefixes of the codeword can tolerate a larger fraction of errors. A rateless code achieves capacity for a family of channels if, for every channel in the family, reliable communication is obtained by a prefix of the code whose rate is arbitrarily close to the channel's capacity. As a result, a universal encoder can communicate over all channels in the family while simultaneously achieving optimal communication overhead. In this paper, we construct the first \emph{deterministic} rateless code for the binary symmetric channel. Our code can be encoded and decoded in O(β)O(\beta) time per bit and in almost logarithmic parallel time of O(βlogn)O(\beta \log n), where β\beta is any (arbitrarily slow) super-constant function. Furthermore, the error probability of our code is almost exponentially small exp(Ω(n/β))\exp(-\Omega(n/\beta)). Previous rateless codes are probabilistic (i.e., based on code ensembles), require polynomial time per bit for decoding, and have inferior asymptotic error probabilities. Our main technical contribution is a constructive proof for the existence of an infinite generating matrix that each of its prefixes induce a weight distribution that approximates the expected weight distribution of a random linear code

    Asymptotic stability of stochastic differential equations driven by Lévy noise

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    Using key tools such as Ito's formula for general semimartingales, Kunita's moment estimates for Levy-type stochastic integrals, and the exponential martingale inequality, we find conditions under which the solutions to the stochastic differential equations (SDEs) driven by Levy noise are stable in probability, almost surely and moment exponentially stable

    Asymptotic stability of stochastic differential equations driven by Lévy noise

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    Using key tools such as Ito's formula for general semimartingales, Kunita's moment estimates for Levy-type stochastic integrals, and the exponential martingale inequality, we find conditions under which the solutions to the stochastic differential equations (SDEs) driven by Levy noise are stable in probability, almost surely and moment exponentially stable
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