帧正则序列

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED
Pu-Ting Yu
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引用次数: 0

摘要

让 H 是可分离的希尔伯特空间,让 \(\{x_{n}\} 是 H 中不包含任何零元素的序列。如果归一化序列({\bigl \{frac{x_n}{Vert x_n\Vert }\bigr \}}\ )分别是一个贝塞尔序列或H的一个框架,我们就说\(\{x_{n}\})是一个贝塞尔可归一化序列或框架可归一化序列。本文证明了序列可框架归一化和不可框架归一化的几个必要条件和充分条件。本文还证明了可框架归一化序列的扰动定理。作为应用,我们证明了贝塞尔正则化序列的巴拉兹-斯托瓦猜想成立。最后,我们运用我们的结果部分地回答了阿尔德鲁比等人提出的开放问题:与正态算子\(A:H\rightarrow H\)和H的可数子集S相关联的迭代系统({\frac{A^{n} x}{Vert A^{n}x\Vert }\bigr \}_{n\ge 0,\,x\in S}\)是否是H的框架。特别地,如果S是有限的,那么我们就能够证明,只要(\{A^{n}x}{Vert A^{n}x\Vert }\bigr \}_{n\ge 0,\,x\in S}\) 是H的框架,那么\(\{A^{n}x\}_{n\ge 0,\,x\in S}\) 就不是H的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Frame-normalizable sequences

Let H be a separable Hilbert space and let \(\{x_{n}\}\) be a sequence in H that does not contain any zero elements. We say that \(\{x_{n}\}\) is a Bessel-normalizable or frame-normalizable sequence if the normalized sequence \({\bigl \{\frac{x_n}{\Vert x_n\Vert }\bigr \}}\) is a Bessel sequence or a frame for H, respectively. In this paper, several necessary and sufficient conditions for sequences to be frame-normalizable and not frame-normalizable are proved. Perturbation theorems for frame-normalizable sequences are also proved. As applications, we show that the Balazs–Stoeva conjecture holds for Bessel-normalizable sequences. Finally, we apply our results to partially answer the open question raised by Aldroubi et al. as to whether the iterative system \(\bigl \{\frac{A^{n} x}{\Vert A^{n}x\Vert }\bigr \}_{n\ge 0,\, x\in S}\) associated with a normal operator \(A:H\rightarrow H\) and a countable subset S of H, is a frame for H. In particular, if S is finite, then we are able to show that \(\bigl \{\frac{A^{n} x}{\Vert A^{n}x\Vert }\bigr \}_{n\ge 0,\, x\in S}\) is not a frame for H whenever \(\{A^{n}x\}_{n\ge 0,\,x\in S}\) is a frame for H.

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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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