[Pattern recognition applied to the fingerprint of traditional Chinese medicine characterized by two-dimension information data].
OBJECTIVE
To establish the two-dimension information fingerprints chromatograph of traditional Chinese medicine and investigate via pattern recognition.


METHODS
Hierarchical cluster was applied to fingerprints described by one-dimension information data and by two-dimension information data respectively and corresponding results was compared.


RESULTS
The gross classes, in which the samples denoted by two-dimension information data, classified by all kinds of hierarchical cluster methods had less differences and more robustness than the methods containing the samples expressed by one-dimension information data. The classes to which the unknown samples would be belonged were determined by hierarchical cluster analysis and artificial neural network (ANN), and the same results were obtained.


CONCLUSIONS
The fingerprints characterized by two-dimension information data could provide more overall and special information as compared with the methods indicated by one-dimension information data.
Nie
Lei
L
Pharmic Institute of Tsinghua University, Beijing 100084, China.
Luo
Guo-an
GA
Cao
Jin
J
Wang
Yi-ming
YM
D002851:Chromatography, High Pressure Liquid / Q000379:methods; D016000:Cluster Analysis; D004365:Drugs, Chinese Herbal / Q000737:chemistry* / Q000302:isolation & purification; D005419:Flavonoids / Q000737:chemistry / Q000302:isolation & purification; D020441:Ginkgo biloba / Q000737:chemistry; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D010598:Pharmacognosy; D010946:Plants, Medicinal / Q000737:chemistry* / Q000145:classification; D013045:Species Specificity
D004365:Drugs, Chinese Herbal; D005419:Flavonoids