Fast Convergence Method for Scaling Window Sidelobe Magnitude

Yong Lim, Tapio Saramäki, Paulo S.R. Diniz, Qinglai Liu

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Windows such as Dolph-Chebyshev window and Kaiser window are adjustable, whereas windows such as Hamming window and Blackman window are traditionally not adjustable. In [1], a technique for trading off main lobe width against sidelobe magnitude for any arbitrary window, including the traditionally non-adjustable windows, was presented. However, the method in [1] requires a large number of iterations if the specification is very tight. Developed based on a new perspective on the window adjustment principle, a new method to achieve the same adjustment capability as in [1], but at a very much fewer iterations is presented in this letter. Our new method is particular useful if the specification is very tight.

Original languageEnglish
Pages (from-to)2078-2081
Number of pages4
JournalIEEE Signal Processing Letters
Volume28
DOIs
Publication statusPublished - 2021
Publication typeA1 Journal article-refereed

Keywords

  • Chebyshev approximation
  • Convergence
  • Indexes
  • Laboratories
  • main lobe sidelobe tradeoff
  • main lobe width
  • Shape
  • sidelobe magnitude
  • Signal processing
  • Signal processing algorithms
  • Window

Publication forum classification

  • Publication forum level 2

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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