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Universal minimum-rate sampling and spectrum-blind reconstruction for multiband signals.

机译:多频带信号的通用最小速率采样和频谱盲重构。

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摘要

Various aspects concerning the proposed theory of spectrum-blind sampling of multi-band signals and related pattern and algorithm design issues are investigated in this dissertation. Traditionally, sampling pattern design and signal reconstruction fully depend on the knowledge of spectral support. In contrast, our approach assumes minimal knowledge about the spectral support (i.e., spectral occupancy rate and end-points of the spectral span, but not band structure, which has been vital for traditional approaches), thus enabling potential applications in diverse fields from data compression to Fourier imaging, to array processing and communications, which may not have been possible.;As far as we know, all work to date is still concentrated on spectral support dependent reconstruction, although the universality of the ill-conditioned bunched sampling pattern has been mentioned. Our approach combines well-conditioned universality, alias-resolving capability and spectrum-blind reconstructibility, and is capable of approaching the Landau-Nyquist minimum sampling rate, closing a fundamental gap in the Shannon sampling theory in the treatment of the widely used general class of multiband signals.;The dissertation includes three parts: (1) one-dimensional theory and design, (2) two-dimensional theory and design (which is readily extendable to higher dimensions), and (3) application to Fourier imaging. The proposed spectrum-blind sampling and reconstruction theory addresses issues like existence and optimal design of universal sampling patterns and their conditioning, algorithms and uniqueness conditions for optimal spectral support recovery, as well as algorithms, uniqueness conditions and other properties of signal reconstruction via a multiresolution approach. The investigations are conducted in the framework of the proposed multicoset sampling theory, employing a periodic nonuniform sampling pattern and noniterative multirate reconstruction schemes that combine the capability of nonuniform sampling and the ease of implementation of uniform sampling.
机译:本文研究了与多频带信号的频谱盲采样理论有关的各个方面以及相关的模式和算法设计问题。传统上,采样模式设计和信号重建完全取决于频谱支持的知识。相比之下,我们的方法假设对频谱支持的了解最少(即,频谱占用率和频谱跨度的终点,但对传统方法至关重要的不是波段结构),因此可以利用数据在各种领域中进行潜在的应用压缩到傅立叶成像,再到阵列处理和通信,这可能是不可能的;据我们所知,尽管病态成束采样模式具有普遍性,但迄今为止,所有工作仍集中在依赖光谱支持的重建上被提及。我们的方法结合了条件良好的通用性,混叠解析能力和频谱盲可重构性,并能够达到Landau-Nyquist最小采样率,从而弥补了Shannon采样理论在广泛使用的通用分类中的根本缺陷。论文包括三个部分:(1)一维理论和设计;(2)二维理论和设计(可以很容易地扩展到更高的维度);(3)在傅立叶成像中的应用。提出的频谱盲采样和重构理论解决了诸如通用采样模式的存在和最佳设计及其条件,用于最佳频谱支持恢复的算法和唯一性条件以及通过多分辨率进行信号重构的算法,唯一性条件和其他属性等问题方法。研究是在提出的多陪集抽样理论的框架下进行的,采用了周期性的非均匀抽样模式和非迭代的多速率重建方案,这些方案结合了非均匀抽样的能力和易于实施的统一抽样。

著录项

  • 作者

    Feng, Ping.;

  • 作者单位

    University of Illinois at Urbana-Champaign.;

  • 授予单位 University of Illinois at Urbana-Champaign.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 1998
  • 页码 99 p.
  • 总页数 99
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:48:45

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