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文章基本信息

  • 标题:Generalized Parseval’s Theorem on Fractional Fourier Transform for Discrete Signals and Filtering of LFM Signals
  • 本地全文:下载
  • 作者:Xiaotong Wang ; Guanlei Xu ; Yue Ma
  • 期刊名称:Journal of Signal and Information Processing
  • 印刷版ISSN:2159-4465
  • 电子版ISSN:2159-4481
  • 出版年度:2013
  • 卷号:4
  • 期号:3
  • 页码:274-281
  • DOI:10.4236/jsip.2013.43035
  • 出版社:Scientific Research Publishing
  • 摘要:This paper investigates the generalized Parseval’s theorem of fractional Fourier transform (FRFT) for concentrated data. Also, in the framework of multiple FRFT domains, Parseval’s theorem reduces to an inequality with lower and upper bounds associated with FRFT parameters, named as generalized Parseval’s theorem by us. These results theoretically provide potential valuable applications in filtering, and examples of filtering for LFM signals in FRFT domains are demonstrated to support the derived conclusions.
  • 关键词:Discrete Fractional Fourier Transform (DFRFT); Uncertainty Principle; Frequency-Limiting Operator; Linear Frequency-Modulation (LFM) Signal; Filtering
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