Adapting matching pursuit dictionaries to waveform structure using particle filtering

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Although the matching pursuit algorithm can accurately decompose waveforms, its use in real applications is limited. This is because it can be computationally intensive as it is based on selecting elements from complete dictionaries spanning the time-frequency plane of interest. There is, therefore, a need for smaller dictionaries that can still result in accurate waveform decompositions. In this paper, we propose the particle filter matching pursuit algorithm that adapts the dictionary to the waveform structure. This algorithm uses particle filtering, a sequential Monte Carlo approach, to estimate the dictionary suitable for the decomposition of a given waveform, and then uses the matching pursuit algorithm to decompose the waveform. We demonstrate, using simulations, that the particle filtering matching pursuit can decompose waveforms faster than the matching pursuit.

Original languageEnglish (US)
Title of host publication2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
Pages561-565
Number of pages5
StatePublished - Dec 1 2006
Event4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006 - Waltham, MA, United States
Duration: Jul 12 2006Jul 14 2006

Publication series

Name2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006

Other

Other4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
CountryUnited States
CityWaltham, MA
Period7/12/067/14/06

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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