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Time-frequency decomposition of band-limited signals with BMFLC and Kalman filter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Time-Frequency analysis of band-limited signals received significant attention in biomedical research. As most bio-signals are non-stationary, time-frequency analysis is essential to analyze the characteristics of the signal. To accurately model the band-limited bio-signal, band-limited multiple Fourier linear combiner (BMFLC), a linear combination of truncated multiple Fourier series models is employed. A state-space model for BMFLC in combination with Kalman filter/smoother is developed to obtain accurate adaptive estimation. By virtue of construction, BMFLC with Kalman filter provides accurate time-frequency decomposition of the bandlimited signal. To evaluate the proposed algorithm, a comparison with short-time Fourier transform (STFT) and continuous wavelet transform (CWT) for synthesized data is performed in this paper. The results show that the proposed algorithm can provide optimal time-frequency resolution as compared to STFT and CWT.

Original languageEnglish
Title of host publicationProceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Pages582-587
Number of pages6
DOIs
StatePublished - 2012
Event2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 - Singapore, Singapore
Duration: 18 Jul 201220 Jul 2012

Publication series

NameProceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

Conference

Conference2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Country/TerritorySingapore
CitySingapore
Period18/07/1220/07/12

Keywords

  • Adaptive Filter
  • Band Limited Multiple Fourier Linear Combiner
  • Kalman Filter
  • Time-Frequency analysis

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