A sliding-window online fast variational sparse Bayesian learning algorithm

Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor

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

3 Scopus citations

Abstract

In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for inclusion or deletion of basis functions is obtained by applying a recently proposed fast variational sparse Bayesian learning (SBL) method. The proposed scheme uses a sliding window estimator to process the data in an online fashion. The noise variance can be implicitly estimated by the algorithm. It is shown that the described method has better mean square error (MSE) performance than a state of the art kernel recursive least squares (Kernel-RLS) algorithm when using the same number of basis functions.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
Pages2128-2131
Number of pages4
DOIs
StatePublished - Aug 18 2011
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: May 22 2011May 27 2011

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
CountryCzech Republic
CityPrague
Period5/22/115/27/11

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Variational inference
  • online learning
  • sparse Bayesian learning

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  • Cite this

    Buchgraber, T., Shutin, D., & Poor, H. V. (2011). A sliding-window online fast variational sparse Bayesian learning algorithm. In 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings (pp. 2128-2131). [5946747] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2011.5946747