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Improved Type-Based Detection of Analog Signals

Authors :
Paulo Gonçalves
Don H. Johnson
Richard G. Baraniuk
Electrical and Computer Engineering - Rice University
Rice University [Houston]
Laboratoire de l'Informatique du Parallélisme (LIP)
École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL)
Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)
Gonçalves, Paulo
École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL)
Source :
IEEE Int. Conf. on Acoust. Speech and Sig. Proc., IEEE Int. Conf. on Acoust. Speech and Sig. Proc., Apr 1997, Munich, Germany, ICASSP
Publication Year :
1997
Publisher :
HAL CCSD, 1997.

Abstract

When applied to continuous-time observations, type-based detection strategies are limited by the necessity to crudely quantize each sample. To alleviate this problem, we smooth the types for both the training and observation data with a linear filter. This post-processing improves the detector performance significantly (error probabilities decrease by over a factor of three) without incurring a significant computational penalty. However this improvement depends on the amplitude distribution and on the quantizer's characteristics.

Details

Language :
English
Database :
OpenAIRE
Journal :
IEEE Int. Conf. on Acoust. Speech and Sig. Proc., IEEE Int. Conf. on Acoust. Speech and Sig. Proc., Apr 1997, Munich, Germany, ICASSP
Accession number :
edsair.doi.dedup.....712a2ce55061603c36f3ef910fa07eea