OBJECTIVEA new pattern recognition method suitable for traditional Chinese patent medicine was established in this paper, which is named as the Dual index grade sequence pattern recognition.

METHODIn this method the quality gradation was defined mathematically relying on normal distribution. By this way samples can be clustered and classified depending on which quality gradation is wanted, and the grading samples quantitatively relative to quality can be performed simultaneously. Especially, the redundant information with respect to pattern recognition hiding in dual index sequences of samples can be removed effectively by applying the good grade sequences, which make the pattern recognition results accurate excellently. This approach possesses the advantages of both supervised classification and unsupervised cluster methods. Samples can be clustered and classified at the same time without any standard samples, and the operation is accomplished based on the good grade similar sequences themselves being as the classifying marks. Moreover, the subclasses in each class can be identified more subtly.

RESULTThe infrared fingerprint spectra of extracts of 27 kinds of Mingmu Dihuangwan pills and Zhibo Dihuangwan pills samples extracted with ethanol were analyzed with the method proposed in this paper. The results showed that these pills can be classified in their subclasses clearly, respectively.

CONCLUSIONThe Dual index grade sequence pattern recognition is a new and effective one for identifying complex biological products made from complex herbal medicines.