通过随机过程首次达到给定水平

IF 2.2 3区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Transactions on Information Theory Pub Date : 2024-08-15 DOI:10.1109/TIT.2024.3444043
Sergei L. Semakov
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引用次数: 0

摘要

我们提出了一种方法,用于计算与随机过程越级相关的事件概率。利用这个方案,我们可以估算出一个 n 维连续过程 ${mathbf { y}}(x)\!=\ 的分量 $y_{1}(x)$ 首次达到给定水平的概率!\{y_{1}(x),\ldots,y_{n}(x)\}$发生在给定区间$(x',x''')$的某个时刻$x^{*}$,并且在这个时刻$x^{*}$,其他分量$y_{2}(x^{*}),\ldots,y_{n}(x^{*})$满足给定的约束条件。在确保飞机着陆安全的问题中,尤其需要估算上述概率。
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The First Achievement of a Given Level by a Random Process
We propose a scheme for finding the probabilities of events related to crossings of a level by a random process. Using this scheme, we estimate the probability that the first achievement of a given level by the component $y_{1}(x)$ of an n-dimensional continuous process ${\mathbf { y}}(x)\!=\!\{y_{1}(x),\ldots,y_{n}(x)\}$ occurs at some moment $x^{*}$ from a given interval $(x',x'')$ and, at this moment $x^{*}$ , the other components $y_{2}(x^{*}),\ldots,y_{n}(x^{*})$ satisfy given constraints. The need for estimating the above-mentioned probability arises, in particular, in the problems of ensuring the safety of an aircraft landing.
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来源期刊
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory 工程技术-工程:电子与电气
CiteScore
5.70
自引率
20.00%
发文量
514
审稿时长
12 months
期刊介绍: The IEEE Transactions on Information Theory is a journal that publishes theoretical and experimental papers concerned with the transmission, processing, and utilization of information. The boundaries of acceptable subject matter are intentionally not sharply delimited. Rather, it is hoped that as the focus of research activity changes, a flexible policy will permit this Transactions to follow suit. Current appropriate topics are best reflected by recent Tables of Contents; they are summarized in the titles of editorial areas that appear on the inside front cover.
期刊最新文献
Table of Contents IEEE Transactions on Information Theory Publication Information IEEE Transactions on Information Theory Information for Authors Large and Small Deviations for Statistical Sequence Matching Derivatives of Entropy and the MMSE Conjecture
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