UMR 5224


Brigitte Bidégaray-Fesquet — Non-uniform signal processing

Partners

LJK Brigitte Bidégaray-Fesquet
TIMA Laurent Fesquet, Gilles Sicard, and Taha Beyrouthy,
and formerly Fabien Aeschlimann, Saeed Mian Qaisar
Gipsa-Lab Nicolas Marchand, Christophe Prieur

Previous work

Most electronic systems have a clock which synchronises everything. A numerical electronic signal is therefore usually synchronous and corresponds to data at times which are all multiples of a unique sampling time. Classical signal processing is strongly based on this property.

The CIS team of the TIMA laboratory in Grenoble develops asynchronous (i.e. clock-less) processors for which samples are collected each time some event occurs, such as level-crossing of an analog signal. For these asynchronous processors, all the usual tools of microelectrnics have to be rebuilt, in particular signal processing chains.

For a few years there has been a first informal collaboration between the LJK and TIMA laboratory on non-uniform signal processing. We have the support of the M-STIC pole of the Joseph Fourier University: TATIE project (Technologie Asynchrone et Traitement des signaux Irrégulièrement Echantillonnés, 2009–2010) and OASIS project (Ondelettes et Analyse Statistique d'échantillons Induits par le Signal, 2012–2013). We have a certain number of common results:

  • the application of usual IIR filters to non-uniform signals: [FB10], following Fabien Aeschlimann PhD [Aes06],
  • the design of asynchronous filters (sampled in frequency): [BF09], [BF11a], [BF11b], [BF12],
  • the analysis of low-consumption algorithms: [FSB10],
  • a Matalab toolbox SPASS (Signal Processing for ASynchronous Systems) which implements all the algorithms we have developed.

Ongoing work

We are currently working on

  • a new more robust version of the SPASS toolbox,
  • the comparison of fully non-uniform algorithms with resampling techniques of active parts of a sporadic signal developped in Saeed Mian Qaisar's PhD [Qai09],
  • the mathematical (and statistical analysis) of the previouly developed algorithms [BC13], [BC14],
  • the analysis of the reconstruction of a non-uniform signal,
  • the extension of mathematical results to level-crossing sampling problems in control, in collaboration with the Gipsa-Lab in Grenoble.

References

[Aes06] Fabien Aeschlimann. Traitement du signal échantillonné non uniformément : algorithme et architecture. PhD thesis, INP Grenoble, February 2006.
[BC13] Brigitte Bidégaray-Fesquet and Mariane Clausel. Level crossing sampling of strongly monoHölder functions. 10th International Conference on Sampling Theory and Applications (SampTa'13), Bremen, Germany, 2013.
[BC14] Brigitte Bidégaray-Fesquet and Marianne Clausel. Data driven sampling of oscillating signals. Sampling Theory in Signal and Image Processing, 13, 175–187, 2014.
[BF09] Brigitte Bidégaray-Fesquet and Laurent Fesquet. A fully non-uniform approach to FIR filtering. 8th International Conference on Sampling Theory and Applications (SampTa'09), Marseille, France, 2009.
[BF11a] Brigitte Bidégaray-Fesquet and Laurent Fesquet. Non-uniform filter interpolation in the frequency domain. Sampling Theory in Signal and Image Processing, 10, 17–35, 2011.
[BF11b] Brigitte Bidégaray-Fesquet and Laurent Fesquet. Non-uniform filter design in the log-scale. 9th International Conference on Sampling Theory and Applications (SampTa'11), Singapour, 2011
[BF12] Brigitte Bidégaray-Fesquet and Laurent Fesquet. A new synthesis approach for non-uniform filters in the log-scale: proof of concept. submitted to publication, 2012.
[FB10] Laurent Fesquet and Brigitte Bidégaray-Fesquet. IIR Digital Filtering of Non-uniformly Sampled Signals via State Representation. Signal Processing, 90, 2811–2821, 2010.
[FSB10] Laurent Fesquet, Gilles Sicard, and Brigitte Bidégaray-Fesquet. Targeting ultra-low power consumption with non-uniform sampling and filtering. IEEE International Symposium on Circuits and Systems (ISCAS2010), Paris, France. 3585–3588, IEEE, 2010.
[Qai09] Saeed Mian Qaisar. Échantillonnage et traitement conditionnés par le signal : une approche prometteuse pour des traitements efficaces à pas adaptatifs. PhD thesis, INP Grenoble, May 2009.
(Last updated January 2015)