Information-theoretic optimization of chemical sensors

Sensors and Actuators, B: Chemical

Volumn 148, Issue 1, 2010, Pages 298-306

  Vergara, Alexander ^a   Muezzinoglu, Mehmet K ^a   Rulkov, Nikolai ^a   Huerta, Ramon ^a  

^a UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

Gas sensor optimization; Information theory; Kullback Leibler distance; Metal oxide gas sensors; Odor discrimination

Indexed keywords

CLASS SEPARABILITY; CLASSIFICATION PERFORMANCE; FUNDAMENTAL TOOLS; KULLBACK-LEIBLER DISTANCE; METAL OXIDE GAS SENSORS; METAL OXIDE SENSORS; OPERATING PARAMETERS; OPERATING TEMPERATURE; QUANTITATIVE MEASURES; SAMPLE DATASET; SENSING ELEMENTS; SENSOR OPTIMIZATION;

CLASSIFICATION (OF INFORMATION); FIBER OPTIC SENSORS; GAS DETECTORS; GASES; INFORMATION THEORY; METALLIC COMPOUNDS; OPTIMIZATION; SENSORS; TEMPERATURE;

PROBABILITY DISTRIBUTIONS;

EID: 77953914573     PISSN: 09254005     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.snb.2010.04.040     Document Type: Article

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