• DocumentCode
    455101
  • Title

    Sparse Blind Deconvolution Accounting for Time-Shift Ambiguity

  • Author

    Labat, Christian ; Idier, Jérôme

  • Author_Institution
    IRCCyN, ECN, Nantes
  • Volume
    3
  • fYear
    2006
  • fDate
    14-19 May 2006
  • Abstract
    Our contribution deals with blind deconvolution of sparse spike trains. More precisely, we examine the problem in the Markov chain Monte-Carlo (MCMC) framework, where the unknown spike train is modeled as a Bernoulli-Gaussian process. In this context, we point out that time-shift and scale ambiguities jeopardize the robustness of basic MCMC methods, in quite a similar manner to the label switching effect studied by Stephens (2000) in mixture model identification. Finally, we propose proper modifications of the MCMC approach, in the same spirit as Stephens´ contribution
  • Keywords
    Gaussian processes; Markov processes; Monte Carlo methods; deconvolution; Bernoulli-Gaussian process; Markov chain Monte-Carlo framework; sparse blind deconvolution; sparse spike trains; time-shift ambiguity; Additive noise; Bayesian methods; Context modeling; Convolution; Deconvolution; Filters; Gaussian noise; Linear systems; Robustness; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
  • Conference_Location
    Toulouse
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0469-X
  • Type

    conf

  • DOI
    10.1109/ICASSP.2006.1660729
  • Filename
    1660729