A search algorithm of optimal time-frequency atom of gaussian fmmlet transform based on adaptive genetic algorithm

Dian Wei Wang, Yan Jun Li, Ke Zhang, Jun Feng Guo

Research output: Contribution to journalArticlepeer-review

Abstract

Time-frequency analysis method was one of important research areas in the analysis and processing of nonstationary signals and the signal representation method based on the Gaussian FMmlet transform has become an important technique to analyses the signals consists of linear and non-linear frequency-shear components. One of the major problems of the application of Gaussian FMmlet transform in signal processing was its digital realization method of matching pursuit. Aimed at the problems such as low accuracy and poor convergence in existing algorithms, a new optimal Gaussian FMmlet time-frequency atom search method based on the adaptive genetic algorithm was proposed. Firstly a discrete formula of finite length time-frequency atom sequence was derived. Secondly an algorithm based on adaptive genetic algorithm was described in detail. Then a Gaussian FMmlet time-frequency atom search algorithm and its digital implement method based on the adaptive genetic algorithm were presented. Finally a simulation result of practiced example shows that the algorithm not only has high search precision but also has good convergence and robustness.

Original languageEnglish
Pages (from-to)1662-1667
Number of pages6
JournalYuhang Xuebao/Journal of Astronautics
Volume29
Issue number5
StatePublished - Sep 2008

Keywords

  • Adaptive genetic algorithm
  • Adaptive time-frequency distribution
  • Finite length sequence
  • Gaussian FMmlet atom
  • Information processing

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