Reproducing Kernel Hilbert Spaces, Matrix Theory, their relations and applications
再现核希尔伯特空间、矩阵理论、它们的关系和应用
基本信息
- 批准号:RGPIN-2018-04534
- 负责人:
- 金额:$ 2.04万
- 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:2018
- 资助国家:加拿大
- 起止时间:2018-01-01 至 2019-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This proposal consists of several interrelated tasks on fundamental problems in modern complex and functional analysis, matrix analysis and their applications to other fields of mathematics and engineering, e.g., approximation theory, mathematical physics, control theory, signal processing and electrical engineering. Analytic Function Spaces and the operators acting on them has been an active domain of research. RKHS provide a modern and powerful tool to look at such problems, classic and new, and thus they play an important role in numerous domains of applied and pure sciences. The advent of reproducing kernels goes back to the founding works of several prominent mathematicians like Nevanlinna, Pick, and Schur on exact constrained interpolation. Since then, RKHS made evidence of their central role and strength in the study of properties of a wide range of spaces as demonstrated by breakthrough results on interpolation, sampling, uniqueness, and invariant subspaces by Aleman, Carleson, Fricain, Ransford, Richter, Sarason, Seip, etc. The solution in 2013 of the Feichtinger conjecture is a milestone and opens new research directions in the field of reproducing kernels.******We consider several such spaces, e.g., Hardy, Dirichlet, Bergman, Model and de Branges-Rovnyak spaces. The most celebrated operators on these spaces are the forward and backward shift operators. These objects lead to more general concepts like Toeplitz, Hankel operators, Berezin transform and composition operators. Any such operator can be interpreted as an infinite dimensional matrix acting on the sequence space formed with the coefficients of functions in the ambient space. To treat infinite dimensional matrices, we naturally consider their truncations and thus the classical matrix theory shows its face. Hence, looking from this angle, techniques of matrix theory (infinite dimensional as well as finite dimensional) are applied in RKHS. Geometric properties of families of reproducing kernels like completeness, minimality, being a Riesz basis or an asymptotically orthonormal basis, are intimately related to properties like interpolation, sampling, and uniqueness in spaces of holomorphic functions. We are mainly interested here in Hardy, Dirichlet and model spaces and their generalization de Branges-Rovnyak spaces. This leads us to study uniqueness sets and zero sets, cyclicity, and interpolating and sampling sequences in Dirichlet and de Branges-Rovnyak spaces as well as in model subspaces of Hardy spaces. They have natural applications in spectral theory, generalized Hardy spaces, norm control of matrix inversion, and control theory. Moreover, we encounter questions which are interesting in their own right in the subject of matrix theory. A celebrated question, which is the continuation of an old conjecture, is the loci of eigenvalues of doubly-stochastic matrices.**
该提案由几个相互关联的任务组成,涉及现代复杂和泛函分析、矩阵分析及其在数学和工程其他领域(例如逼近论、数学物理、控制理论、信号处理和电气工程)中的应用。分析函数空间和作用于它们的算子一直是一个活跃的研究领域。 RKHS 提供了一个现代而强大的工具来研究此类经典和新问题,因此它们在应用科学和纯科学的众多领域中发挥着重要作用。复制核的出现可以追溯到 Nevanlinna、Pick 和 Schur 等几位著名数学家关于精确约束插值的开创性工作。从那时起,RKHS 证明了他们在广泛空间属性研究中的核心作用和优势,Aleman、Carleson、Fricain、Ransford、Richter、Sarason 在插值、采样、唯一性和不变子空间方面的突破性结果证明了这一点,Seip等。2013年Feichtinger猜想的解决是一个里程碑,开启了再生核领域新的研究方向。******我们考虑了几个这样的空间,例如 Hardy、Dirichlet、Bergman、Model 和 de Branges-Rovnyak 空间。这些空间中最著名的运算符是向前和向后移位运算符。这些对象引出了更一般的概念,如 Toeplitz、Hankel 算子、Berezin 变换和合成算子。任何这样的算子都可以被解释为作用于由周围空间中的函数系数形成的序列空间的无限维矩阵。为了处理无限维矩阵,我们自然会考虑它们的截断,因此经典矩阵理论就显露出来了。因此,从这个角度来看,RKHS中应用了矩阵理论(无限维和有限维)技术。再生核族的几何性质,如完整性、极小性、作为 Riesz 基或渐近正交基,与全纯函数空间中的插值、采样和唯一性等性质密切相关。我们主要对 Hardy、Dirichlet 和模型空间以及它们的 Branges-Rovnyak 空间的推广感兴趣。这引导我们研究狄利克雷空间和 de Branges-Rovnyak 空间以及 Hardy 空间的模型子空间中的唯一性集和零集、循环性以及插值和采样序列。它们在谱理论、广义 Hardy 空间、矩阵求逆的范数控制和控制理论中具有天然的应用。此外,我们在矩阵理论中遇到了一些本身就很有趣的问题。一个著名的问题是双随机矩阵特征值的轨迹,它是一个古老猜想的延续。**
项目成果
期刊论文数量(0)
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{{ truncateString('Mashreghi, Javad', 18)}}的其他基金
Reproducing Kernel Hilbert Spaces, Matrix Theory, their relations and applications
再现核希尔伯特空间、矩阵理论、它们的关系和应用
- 批准号:
RGPIN-2018-04534 - 财政年份:2022
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Reproducing Kernel Hilbert Spaces, Matrix Theory, their relations and applications
再现核希尔伯特空间、矩阵理论、它们的关系和应用
- 批准号:
RGPIN-2018-04534 - 财政年份:2021
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Reproducing Kernel Hilbert Spaces, Matrix Theory, their relations and applications
再现核希尔伯特空间、矩阵理论、它们的关系和应用
- 批准号:
RGPIN-2018-04534 - 财政年份:2020
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Reproducing Kernel Hilbert Spaces, Matrix Theory, their relations and applications
再现核希尔伯特空间、矩阵理论、它们的关系和应用
- 批准号:
RGPIN-2018-04534 - 财政年份:2019
- 资助金额:
$ 2.04万 - 项目类别:
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$ 2.04万 - 项目类别:
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再现核希尔伯特空间、矩阵理论、它们的关系和应用
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Discovery Grants Program - Individual
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