高强度条件下射弹噪声过程的采样路径适度偏差

IF 1.1 2区 数学 Q3 STATISTICS & PROBABILITY
Sumith Reddy Anugu, Guodong Pang
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引用次数: 0

摘要

我们研究了高强度状态下射弹噪声过程的采样路径适度偏差原理(MDP)。射出噪声过程具有更新到达过程、非稳态噪声(与到达时间相关的分布)和噪声的一般射出响应函数。MDP 中的速率函数在这种渐近机制中表现出记忆现象,这与传统时空缩放机制中的记忆现象截然不同。为了证明采样路径 MDP,我们首先确定这等同于建立另一个更容易研究的过程的采样路径 MDP。我们证明了它的有限维 MDP,然后建立了 Skorohod J1 拓扑下的指数紧密性。这就得到了 Skorohod J1 拓扑下 D 中的样本路径 MDP,其速率函数是利用重现核希尔伯特空间工具从有限维 MDP 的速率函数导出的。在证明中,由于射噪声过程的非稳态性,我们建立了一个新的指数最大不等式,并用它来证明指数紧密性和上述等价性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sample path moderate deviations for shot noise processes in the high intensity regime

We study the sample-path moderate deviation principle (MDP) for shot noise processes in the high intensity regime. The shot noise processes have a renewal arrival process, non-stationary noises (with arrival-time dependent distributions) and a general shot response function of the noises. The rate function in the MDP exhibits a memory phenomenon in this asymptotic regime, which is in contrast with that in the conventional time–space scaling regime. To prove the sample-path MDP, we first establish that this is equivalent to establishing the sample-path MDP of another process that is easier to study. We prove its finite-dimensional MDP and then establish the exponential tightness under the Skorohod J1 topology. This results in the sample-path MDP in D under the Skorohod J1 topology with a rate function that is derived from the rate function in the finite-dimensional MDP using the tools of reproducing kernel Hilbert space. In the proofs, because of the non-stationarity of shot noise process, we establish a new exponential maximal inequality and use it to prove exponential tightness and the aforementioned equivalence.

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来源期刊
Stochastic Processes and their Applications
Stochastic Processes and their Applications 数学-统计学与概率论
CiteScore
2.90
自引率
7.10%
发文量
180
审稿时长
23.6 weeks
期刊介绍: Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.
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