Robust linear dimensionality reduction for hypothesis testing with application to sensor selection

2009 47th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2009

Volumn , Issue , 2009, Pages 363-370

  Bajović, Dragana ^a,b   Sinopoli, Bruno ^b   Xavier, João ^a  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BUILDING BLOCKES; CONFIDENCE REGION; COVARIANCE MATRICES; DATA VECTORS; DETECTOR PERFORMANCE; DISTRIBUTION PARAMETERS; EVENT DETECTION; EXHAUSTIVE SEARCH; FINITE INTERVALS; GAUSSIANS; GRID SEARCH; HIGH DIMENSIONAL SPACES; HYPOTHESIS TESTING; HYPOTHESIS TESTS; KL DISTANCE; KULLBACK-LEIBLER DISTANCE; LINEAR DIMENSIONALITY REDUCTION; LINEAR DISCRIMINANT ANALYSIS; LINEAR MAPPING; LINEAR MAPS; LOW-DIMENSIONAL SPACES; MEAN VALUES; ONE DIMENSION; OPTIMAL SENSOR; QUASI-OPTIMAL; SENSOR SELECTION; TRAINING DATA; WORST CASE;

ALGORITHMS; COVARIANCE MATRIX; DISCRIMINANT ANALYSIS; FACE RECOGNITION; IMAGE RETRIEVAL; OPTIMIZATION; UNCERTAINTY ANALYSIS; VECTOR SPACES;

SENSORS;

EID: 77949620098     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ALLERTON.2009.5394788     Document Type: Conference Paper

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