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Optimal Bi-Level Quantization of i.i.d. Sensor Observations for Binary Hypothesis Testing.
- Source :
- IEEE Transactions on Information Theory; Jul2002, Vol. 48 Issue 7, p2105, 7p, 4 Graphs
- Publication Year :
- 2002
-
Abstract
- Focuses on the use of binary decisions from independent and identically distributed sensors for binary hypothesis testing. Discussion on the Bayesian detection problem; Formulation of the Neyman-Pearson problem; Facts on the use of the SECANT algorithm.
- Subjects :
- HYPOTHESIS
BINARY number system
DEMODULATION
BAYESIAN analysis
ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 00189448
- Volume :
- 48
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Information Theory
- Publication Type :
- Academic Journal
- Accession number :
- 6941692
- Full Text :
- https://doi.org/10.1109/TIT.2002.1013153