Probabilistic symmetries, extreme values and random topology

概率对称性、极值和随机拓扑

基本信息

  • 批准号:
    RGPIN-2020-04356
  • 负责人:
  • 金额:
    $ 1.53万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2021
  • 资助国家:
    加拿大
  • 起止时间:
    2021-01-01 至 2022-12-31
  • 项目状态:
    已结题

项目摘要

Models exhibiting certain distributional symmetries are important topics in probability, and have applications in various disciplines such as physics, astronomy, climatology and oceanography. Commonly used symmetries include stationarity (distributional invariance under translation), self-similarity (distributional invariance under scaling), isotropy (distributional invariance under rotation), etc. Literature shows that some symmetries can lead to specific behavior of the extreme values of the process/random field. Extremes, on the other hand, are closely related to the emerging research area of random topology. It studies the topological properties of random sets such as the excursion set (the area on which the value of a random field is larger than a threshold), and differs from the traditional approaches by focusing on the features which are robust under deformation. The goal of the proposed research is to develop a theory that reveals the relation among probabilistic symmetries, extreme values, and random topology. The research will be pursued as two closely related and interacting streams. The first is to study processes/random fields having probability symmetries defined on various spaces, especially their extremes. I plan to consider the spaces which are compact (S^1, S^n), discrete (Z), or normed differently (p-adic numbers). The second stream will study the topology of the excursion sets for the random fields having probabilistic symmetries. It is strongly motivated by some research in brain imaging, where the excursion sets correspond to the active regions in the brain. The existing results are either asymptotic or for the expected Euler characteristic. I plan to derive bounds for some other important topological quantities, such as the number of the connected components of the excursion sets, for finite thresholds. The proposed research program will contribute significantly in probability and statistics by providing a unified framework to study the extreme values and random topology under probabilistic symmetries. It will lead to a better understanding of the processes defined on different spaces and conversely, the characterization of the spaces using the random locations. Moreover, this will be the first work where bounds are derived for certain topological quantities of the excursion sets. The results are especially useful when topological features are used for data analysis, such as in climatology and oceanography. Finally, the results from the second stream can be directly applied to brain imaging, for example, to detect certain brain illness, so that the patients can get earlier and more precise diagnosis. Thus, these works have potential value for several sectors that are critical to the Canadian public. The students involved will acquire knowledge in probability and related areas as well as skills in problem solving and communication, which prepare them for future career developments.
表现出一定分布对称性的模型是概率论中的重要课题,在物理学、天文学、气候学和海洋学等各个学科中都有应用。常用的对称性包括平稳性(平移下的分布不变性)、自相似性(缩放下的分布不变性)、各向同性(旋转下的分布不变性)等。文献表明,某些对称性可以导致过程/随机场极值的特定行为。另一方面,极值与随机拓扑这一新兴研究领域密切相关。它研究随机集的拓扑性质,如漂移集(随机场的值大于阈值的区域),与传统方法不同,它关注的是形变下的鲁棒性特征。提出的研究目标是发展一种理论,揭示概率对称性、极值和随机拓扑之间的关系。研究将作为两个密切相关和相互作用的流进行。第一种是研究在不同空间上具有概率对称性的过程/随机场,特别是它们的极值。我计划考虑紧凑(S^1, S^n),离散(Z)或不同赋范(p进数)的空间。第二部分将研究具有概率对称性的随机场偏移集的拓扑结构。它是由脑成像的一些研究强烈推动的,其中偏移集对应于大脑中的活跃区域。现有的结果要么是渐近的,要么是符合预期的欧拉特征的。我计划推导一些其他重要的拓扑量的边界,例如有限阈值的偏移集的连接分量的数量。本研究为研究概率对称下的极值和随机拓扑提供了一个统一的框架,将对概率论和统计学有重要的贡献。这将有助于更好地理解在不同空间上定义的过程,反过来,利用随机位置对空间进行表征。此外,这将是第一个导出偏移集的某些拓扑量的界的工作。当将拓扑特征用于数据分析时,例如在气候学和海洋学中,这些结果特别有用。最后,第二流的结果可以直接应用于脑成像,例如检测某些脑部疾病,从而使患者得到更早、更准确的诊断。因此,这些作品对加拿大公众至关重要的几个部门具有潜在价值。参与的学生将获得概率和相关领域的知识,以及解决问题和沟通的技能,为他们未来的职业发展做好准备。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Shen, Yi其他文献

Long non-coding RNA MALAT1 regulates retinal neurodegeneration through CREB signaling.
  • DOI:
    10.15252/emmm.202216660
  • 发表时间:
    2022-12-07
  • 期刊:
  • 影响因子:
    11.1
  • 作者:
    Yao, Jin;Wang, Xiao-Qun;Li, Yu-Jie;Shan, Kun;Yang, Hong;Wang, Yang-Ning-Zhi;Yao, Mu-Di;Liu, Chang;Li, Xiu-Miao;Shen, Yi;Liu, Jing-Yu;Cheng, Hong;Yuan, Jun;Zhang, Yang-Yang;Jiang, Qin;Yan, Biao
  • 通讯作者:
    Yan, Biao
Global exponential stability in a Lagrange sense for memristive recurrent neural networks with time-varying delays
具有时变延迟的忆阻循环神经网络拉格朗日意义上的全局指数稳定性
  • DOI:
    10.1016/j.neucom.2014.08.064
  • 发表时间:
    2015-02
  • 期刊:
  • 影响因子:
    6
  • 作者:
    Zhang, Guodong;Shen, Yi;Xu, Chengjie
  • 通讯作者:
    Xu, Chengjie
Asynchronous finite-time H-infinity control for switched linear systems via mode-dependent dynamic state-feedback
通过依赖于模式的动态状态反馈对切换线性系统进行异步有限时间 H 无穷大控制
Robust H(infinity) Control for Stochastic Markovian Jupp Systems
随机马尔可夫Jupp系统的鲁棒H(无穷大)控制
Almost sure exponential stability of backward EulerMaruyama discretizations for hybrid stochastic differential equations
混合随机微分方程后向 EulerMaruyama 离散化的几乎确定的指数稳定性

Shen, Yi的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Shen, Yi', 18)}}的其他基金

Probabilistic symmetries, extreme values and random topology
概率对称性、极值和随机拓扑
  • 批准号:
    RGPIN-2020-04356
  • 财政年份:
    2022
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Discovery Grants Program - Individual
Probabilistic symmetries, extreme values and random topology
概率对称性、极值和随机拓扑
  • 批准号:
    RGPIN-2020-04356
  • 财政年份:
    2020
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Discovery Grants Program - Individual
Characterizing Stationarities Using Distributions of Random Locations
使用随机位置的分布表征平稳性
  • 批准号:
    RGPIN-2014-04840
  • 财政年份:
    2019
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Discovery Grants Program - Individual
Characterizing Stationarities Using Distributions of Random Locations
使用随机位置的分布表征平稳性
  • 批准号:
    RGPIN-2014-04840
  • 财政年份:
    2017
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Discovery Grants Program - Individual
Characterizing Stationarities Using Distributions of Random Locations
使用随机位置的分布表征平稳性
  • 批准号:
    RGPIN-2014-04840
  • 财政年份:
    2016
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Discovery Grants Program - Individual
Characterizing Stationarities Using Distributions of Random Locations
使用随机位置的分布表征平稳性
  • 批准号:
    RGPIN-2014-04840
  • 财政年份:
    2015
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Discovery Grants Program - Individual
Characterizing Stationarities Using Distributions of Random Locations
使用随机位置的分布表征平稳性
  • 批准号:
    RGPIN-2014-04840
  • 财政年份:
    2014
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Discovery Grants Program - Individual

相似海外基金

REU Site: Research in Symmetries at the University of Kentucky
REU 网站:肯塔基大学对称性研究
  • 批准号:
    2349261
  • 财政年份:
    2024
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Continuing Grant
Geometric evolution of spaces with symmetries
具有对称性的空间的几何演化
  • 批准号:
    DP240101772
  • 财政年份:
    2024
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Discovery Projects
CAREER: Symmetries and Classical Physics in Machine Learning for Science and Engineering
职业:科学与工程机器学习中的对称性和经典物理学
  • 批准号:
    2339682
  • 财政年份:
    2024
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Continuing Grant
Lagrangian Multiforms for Symmetries and Integrability: Classification, Geometry, and Applications
对称性和可积性的拉格朗日多重形式:分类、几何和应用
  • 批准号:
    EP/Y006712/1
  • 财政年份:
    2024
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Fellowship
Canonical Singularities, Generalized Symmetries, and 5d Superconformal Field Theories
正则奇点、广义对称性和 5d 超共形场论
  • 批准号:
    EP/X01276X/1
  • 财政年份:
    2023
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Fellowship
Characterization of Systematic Effects in Ultracold Neutron Tests of Fundamental Symmetries
基本对称性超冷中子测试中系统效应的表征
  • 批准号:
    2310015
  • 财政年份:
    2023
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Standard Grant
Research in Novel Symmetries of Quantum Field Theory and String Theory
量子场论和弦理论的新对称性研究
  • 批准号:
    2310279
  • 财政年份:
    2023
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Continuing Grant
Categorical Symmetries of Operator Algebras
算子代数的分类对称性
  • 批准号:
    2247202
  • 财政年份:
    2023
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Standard Grant
CAREER: Low-energy Nuclear Physics and Fundamental Symmetries with Neutrons and Cryogenic Technologies
职业:低能核物理以及中子和低温技术的基本对称性
  • 批准号:
    2232117
  • 财政年份:
    2023
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Continuing Grant
Random curves and surfaces with conformal symmetries
具有共形对称性的随机曲线和曲面
  • 批准号:
    2246820
  • 财政年份:
    2023
  • 资助金额:
    $ 1.53万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了