@inproceedings{cha-hil-che-12-aa-dsp,
  author = {Chapoutot, Alexandre and Hilaire, Thibault and Chevrel, Philippe},
  title = {Interval-based Robustness of Linear Parametrized Filters},
  booktitle = {5th GAMM-IMACS International Symposium on Scientific Computing, Computer Arithmetic and Verified Numerical Computations (SCAN)},
  location = {Novosibirsk, RU},
  year = 2012,
  month = sep,
  url = {https://hal.archives-ouvertes.fr/hal-00706772},
  note = {No page numbers? No DOI?},
  comment = {Uses ``interval optimization methods''. Just IA, or AA?},
  abstract = {This article deals with the resilient implementation of parametrized linear filters (or controllers), i.e. realizations that are robust with respect to their implementation with fixed-point arithmetic. The implementation of a linear filter/controller in an embedded device is a difficult task because the numerical version of such algorithms suff ers from a deterioration in performances and characteristics. This degradation has two separate origins, corresponding to the quantization of the embedded coefficients and the round-off occurring during the computations. The optimal realization problem is to find, for a given filter, the most resilient realization. We here consider linear filters that depends on a set of parameters that are not exactly known during the design. They are used for example in automotive control, where a very late re-tuning is required. The paper presents results on FWL resiliency analyzis using interval optimization methods [2], and compare them to those obtained with the sensitivity approach.}
}