Optimal Bi-level quantization of i.i.d. sensor observations forbinary hypothesis testing

IEEE Transactions on Information Theory

Volumn 48, Issue 7, 2002, Pages 2105-2111

  Zhang, Qian ^a,b   Varshney, Pramod K ^a,c   Wesel, Richard D ^a,d  

^a IEEE   (United States)

^b ANALOG DEVICES INC   (United States)

^c Syracuse University   (United States)

^d University of California   (United States)

Author keywords

Decision making; Multisensor systems; Quantization; Signal detection

Indexed keywords

BINARY HYPOTHESIS TESTING;

ALGORITHMS; DECISION MAKING; ERROR ANALYSIS; LAGRANGE MULTIPLIERS; OPTIMIZATION; PROBABILITY; SIGNAL DETECTION;

SENSOR DATA FUSION;

EID: 0036648167     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIT.2002.1013153     Document Type: Article

References (14)

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8. Decentralized detection
9. Randomized fusion rules can be optimal in distributed Neyman-Pearson detectors