Information, energy and density for ad hoc sensor networks over correlated random fields: Large deviations analysis

IEEE International Symposium on Information Theory - Proceedings

Volumn , Issue , 2008, Pages 1592-1596

  Sung, Youngchul ^a   Yu, Heejung ^a   Poor, H Vincent ^b  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

^b Princeton University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AD-HOC SENSOR NETWORKS; AMOUNT OF INFORMATION; ASYMPTOTIC BEHAVIORS; AUTO REGRESSION; COVERAGE AREAS; FIRST ORDERS; GAUSS-MARKOV RANDOM FIELD; INTERNATIONAL SYMPOSIUM; LARGE DEVIATIONS; NODE DENSITIES; RANDOM FIELD; RANDOM FIELDS; STATISTICAL INFERENCES;

AD HOC NETWORKS; COMPUTATIONAL FLUID DYNAMICS; CONSERVATION; CYBERNETICS; EFFICIENCY; ENERGY EFFICIENCY; GAUSSIAN DISTRIBUTION; HIDDEN MARKOV MODELS; IMAGE SEGMENTATION; INFORMATION THEORY; NEMATIC LIQUID CRYSTALS; RANDOM PROCESSES; REGRESSION ANALYSIS; SENSORS; TECHNICAL PRESENTATIONS; TWO DIMENSIONAL;

SENSOR NETWORKS;

EID: 52349099199     PISSN: 21578101     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIT.2008.4595256     Document Type: Conference Paper

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