The Experts below are selected from a list of 149130 Experts worldwide ranked by ideXlab platform
Toshiyasu Matsushima - One of the best experts on this subject based on the ideXlab platform.
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cumulant Generating Function of codeword lengths in variable length lossy compression allowing positive excess distortion probability
International Symposium on Information Theory, 2018Co-Authors: Shota Saito, Toshiyasu MatsushimaAbstract:This paper considers the problem of variable-length lossy source coding. The performance criteria are the excess distortion probability and the cumulant Generating Function of codeword lengths. We derive a non-asymptotic fundamental limit of the cumulant Generating Function of codeword lengths allowing positive excess distortion probability. It is shown that the achievability and converse bounds are characterized by the Renyi entropy-based quantity. In the proof of the achievability result, the explicit code construction is provided. Further, we investigate an asymptotic single-letter characterization of the fundamental limit for a stationary memoryless source. A full version of this paper is accessible at: http://arxiv.org/abs/1801.02496
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cumulant Generating Function of codeword lengths in variable length lossy compression allowing positive excess distortion probability
arXiv: Information Theory, 2018Co-Authors: Shota Saito, Toshiyasu MatsushimaAbstract:This paper considers the problem of variable-length lossy source coding. The performance criteria are the excess distortion probability and the cumulant Generating Function of codeword lengths. We derive a non-asymptotic fundamental limit of the cumulant Generating Function of codeword lengths allowing positive excess distortion probability. It is shown that the achievability and converse bounds are characterized by the R\'enyi entropy-based quantity. In the proof of the achievability result, the explicit code construction is provided. Further, we investigate an asymptotic single-letter characterization of the fundamental limit for a stationary memoryless source.
Shota Saito - One of the best experts on this subject based on the ideXlab platform.
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cumulant Generating Function of codeword lengths in variable length lossy compression allowing positive excess distortion probability
International Symposium on Information Theory, 2018Co-Authors: Shota Saito, Toshiyasu MatsushimaAbstract:This paper considers the problem of variable-length lossy source coding. The performance criteria are the excess distortion probability and the cumulant Generating Function of codeword lengths. We derive a non-asymptotic fundamental limit of the cumulant Generating Function of codeword lengths allowing positive excess distortion probability. It is shown that the achievability and converse bounds are characterized by the Renyi entropy-based quantity. In the proof of the achievability result, the explicit code construction is provided. Further, we investigate an asymptotic single-letter characterization of the fundamental limit for a stationary memoryless source. A full version of this paper is accessible at: http://arxiv.org/abs/1801.02496
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cumulant Generating Function of codeword lengths in variable length lossy compression allowing positive excess distortion probability
arXiv: Information Theory, 2018Co-Authors: Shota Saito, Toshiyasu MatsushimaAbstract:This paper considers the problem of variable-length lossy source coding. The performance criteria are the excess distortion probability and the cumulant Generating Function of codeword lengths. We derive a non-asymptotic fundamental limit of the cumulant Generating Function of codeword lengths allowing positive excess distortion probability. It is shown that the achievability and converse bounds are characterized by the R\'enyi entropy-based quantity. In the proof of the achievability result, the explicit code construction is provided. Further, we investigate an asymptotic single-letter characterization of the fundamental limit for a stationary memoryless source.
Xiaohu Li - One of the best experts on this subject based on the ideXlab platform.
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some new results on the moment Generating Function order and related life distributions
Journal of Applied Probability, 2010Co-Authors: Shuhong Zhang, Xiaohu LiAbstract:In this paper we study the moment Generating Function order and the new better than used in the moment Generating Function order (NBU MG ) life distributions. A closure property of this order under an independent random sum is deduced, and stochastic comparisons among the block replacement policy, the age replacement policy, the complete repair policy, and the minimal repair policy of an NBU MG component are investigated.
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some properties of ageing notions based on the moment Generating Function order
Journal of Applied Probability, 2004Co-Authors: Xiaohu LiAbstract:Classes of life distributions based on the moment-Generating-Function order are investigated in this paper. It is shown firstly that the class M is closed under both convex linear combination and geometric compounding. Secondly, the class NBU mg (new better than used in the moment-Generating-Function order) is proved to be closed under increasing star-shaped transformations. Finally, the interplay between the stochastic comparison of the excess lifetime of a renewal process and the NBU mg interarrivals is studied.
Yilun Shang - One of the best experts on this subject based on the ideXlab platform.
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joint probability Generating Function for degrees of active passive random intersection graphs
Frontiers of Mathematics in China, 2012Co-Authors: Yilun ShangAbstract:Correlations of active and passive random intersection graphs are studied in this paper. We present the joint probability Generating Function for degrees of Gactive(n, m, p) and Gpassive(n, m, p), which are generated by a random bipartite graph G*(n, m, p) on n + m vertices.
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joint probability Generating Function for degrees of active passive random intersection graphs
arXiv: Combinatorics, 2009Co-Authors: Yilun ShangAbstract:Correlations of active and passive random intersection graphs are studied in this letter. We present the joint probability Generating Function for degrees of $G^{active}(n,m,p)$ and $G^{passive}(n,m,p)$, which are generated by a random bipartite graph $G^*(n,m,p)$ on $n+m$ vertices.
Simos G Meintanis - One of the best experts on this subject based on the ideXlab platform.
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testing skew normality via the moment Generating Function
Mathematical Methods of Statistics, 2010Co-Authors: Simos G MeintanisAbstract:In this paper, goodness-of-fit tests are constructed for the skew normal law. The proposed tests utilize the fact that the moment Generating Function of the skew normal variable satisfies a simple differential equation. The empirical counterpart of this equation, involving the empiricalmoment Generating Function, yields appropriate test statistics. The consistency of the tests is investigated under general assumptions, and the finite-sample behavior of the proposed method is investigated via a parametric bootstrap procedure.
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a kolmogorov smirnov type test for skew normal distributions based on the empirical moment Generating Function
Journal of Statistical Planning and Inference, 2007Co-Authors: Simos G MeintanisAbstract:In this paper tests of hypothesis are constructed for the family of skew normal distributions. The proposed tests utilize the fact that the moment Generating Function of the skew normal variable satisfies a simple differential equation. The empirical counterpart of this equation, involving the empirical moment Generating Function, yields simple consistent test statistics. Finite-sample results as well as results from real data are provided for the proposed procedures.
