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921.
Additive convolution of unimodal and α‐unimodal random variables are known as an old classic problem which has attracted the attention of many authors in theory and applied fields. Another type of convolution, called multiplicative convolution, is rather younger. In this article, we first focus on this newer concept and obtain several useful results in which the most important ones is that if is logconcave then so are and for some suitable increasing functions ?. This result contains and as two more important special cases. Furthermore, one table including more applied distributions comparing logconcavity of f(x) and and two comprehensive implications charts are provided. Then, these fundamental results are applied to aging properties, existence of moments and several kinds of ordered random variables. Multiplicative strong unimodality in the discrete case is also introduced and its properties are investigated. In the second part of the article, some refinements are made for additive convolutions. A remaining open problem is completed and a conjecture concerning convolution of discrete α‐unimodal distributions is settled. Then, we shall show that an existing result regarding convolution of symmetric discrete unimodal distributions is not correct and an easy alternative proof is presented. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 109–123, 2016 相似文献
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3D打印技术是一种快速成型技术,在不同领域均有成熟应用。部队现有的技术人才构成、成熟配套的软硬环境、打印材料的多样性,为3D打印技术应用于装备保障训练提供了可能。目前,部队现有的装备保障训练手段仍较为传统、单一,特别是工作原理、故障排除课目很难保证训练效果,严重制约装备保障能力提高。应用3D打印技术,着重对重难点课目进行设计,解决"无法训、训不到、效果差"等训练瓶颈问题,是对现有训练手段的丰富和完善,是继模拟训练、虚拟训练之后的又一新手段、方法,对提高装备训练水平、保证训练质量有重大意义。 相似文献
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This article provides a modeling framework for quantifying cost and optimizing motion plans in combat situations with rapid weapon fire, multiple agents, and attacker uncertainty characterized by uncertain parameters. Recent developments in numerical optimal control enable the efficient computation of numerical solutions for optimization problems with multiple agents, nonlinear dynamics, and a broad class of objectives. This facilitates the application of more realistic, equipment‐based combat models, which track both more realistic models, which track both agent motion and dynamic equipment capabilities. We present such a framework, along with a described algorithm for finding numerical solutions, and a numerical example. 相似文献
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