Galy, Jerome and Chaumette, Eric and Vincent, François and Renaux, Alexandre and Larzabal, Pascal Lower bounds for non standard deterministic estimation. (2016) In: IEEE Sensor Array Multichannel Workshop 2016, 10 July 2016 - 13 July 2016 (Rio de Janeiro, Brazil).
|
(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 108kB |
Official URL: http://dx.doi.org/10.1109/SAM.2016.7569710
Abstract
In this paper, non standard deterministic parameters estimation is considered, i.e. the situation where the probability density function (p.d.f.) parameterized by unknown deterministic parameters results from the marginalization of a joint p.d.f. depending on additional random variables. Unfortunately, in the general case, this marginalization is mathematically intractable, which prevents from using the known deterministic lower bounds on the mean-squared error (MSE). However an embedding mechanism allows to transpose all the known lowers bounds into modified lower bounds fitted with non-standard deterministic estimation, encompassing the modified Cramer-Rao / Bhattacharyya bounds and hybrid lower bounds.
Repository Staff Only: item control page