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Maximum a Posteriori Consistent Estimation Using Interval Analysis

Abstract : This paper presents a MAP estimator for some vector $\mathbf{x}$ from its quantized and noisy linear measurements. The complexity of the optimal MAP estimator is intractable in general, and two suboptimal solutions have been proposed, one of which being iterative to be able to handle large-scale problems. Leveraging on techniques from interval analysis, it is possible to quickly eliminate solutions which are not consistent with the signal model, and the quantization noise. These techniques have been applied to the estimation of the input signal of an OFB using noisy measurements of its quantized subbands. The experimental results show that when the channel is noisy, this approach performs better in terms of reconstruction SNR than classical least-squares reconstruction.
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Contributor : Michel Kieffer Connect in order to contact the contributor
Submitted on : Tuesday, September 4, 2012 - 2:14:21 PM
Last modification on : Thursday, June 17, 2021 - 3:48:42 AM
Long-term archiving on: : Wednesday, December 5, 2012 - 10:04:59 AM


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  • HAL Id : hal-00727521, version 1


Manel Abid, Michel Kieffer, Beatrice Pesquet-Popescu. Maximum a Posteriori Consistent Estimation Using Interval Analysis. SYSID 2012, Jul 2012, Bruxelles, Belgium. pp.1-6. ⟨hal-00727521⟩



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