Large deviations analysis for the detection of 2D hidden Gauss-Markov random fields using sensor networks

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2008, Pages 3893-3896

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

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

^b Princeton University   (United States)

Author keywords

Error exponent; GMRF; Neyman Pearson detection

Indexed keywords

ERROR EXPONENT; ERROR EXPONENTS; GMRF; NEYMAN-PEARSON DETECTION;

ACOUSTIC INTENSITY; ACOUSTICS; COMPUTATIONAL FLUID DYNAMICS; COMPUTER NETWORKS; CORRELATION METHODS; EFFICIENCY; ENERGY EFFICIENCY; ERROR ANALYSIS; GAUSSIAN DISTRIBUTION; HIDDEN MARKOV MODELS; IMAGE SEGMENTATION; MARKOV PROCESSES; REGRESSION ANALYSIS; SENSORS; SIGNAL PROCESSING; SIGNAL TO NOISE RATIO; SPEECH; WIRELESS SENSOR NETWORKS;

SENSOR NETWORKS;

EID: 51449116425     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2008.4518504     Document Type: Conference Paper

References (8)

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