Joint Detection and Decoding in the Presence of Prior Information With Uncertainty

An optimal decision framework is proposed for joint detection and decoding when the prior information is available with some uncertainty. The proposed framework provides tradeoffs between the average inclusive error probability (computed using estimated prior probabilities) and the worst case inclus...

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Veröffentlicht in:	IEEE signal processing letters 2016-11, Vol.23 (11), p.1602-1606
Hauptverfasser:	Bayram, Suat, Dulek, Berkan, Gezici, Sinan
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayes Bayes methods Decoding detection Detectors Neyman–Pearson Optimization Testing Transmitters Uncertainty
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