Title :
A consensus structure inference algorithm
Author_Institution :
Dept. of Comput. & Inf. Sci., Guelph Univ., Ont., Canada
Abstract :
The notion of consensus structure, a special form of random graph, is formally defined. The consensus structure represents an extended higher-order representation of the random n-tuple for statistical and structural pattern recognition. An algorithm inferring the consensus structure from a random n-tuple is designed based on the detection of statistical interdependency under certain structural constraints. In applying structural constraints, a circular diagram indicating variable interaction is used to extract global structural features in a macromolecular modeling problem
Keywords :
graph theory; pattern recognition; spatial reasoning; statistical analysis; circular diagram; consensus structure inference algorithm; extended higher-order representation; global structural features; macromolecular modeling; random graph; random n-tuple; statistical interdependency; structural pattern recognition; Algorithm design and analysis; Entropy; Feature extraction; Inference algorithms; Information analysis; Information science; Mutual information; Pattern recognition; Testing;
Conference_Titel :
Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
Conference_Location :
Maui, HI
Print_ISBN :
0-8186-2148-6
DOI :
10.1109/CVPR.1991.139815
