Fuzzing Pattern Recognition Study on Ramam Spectrum of Tumor Peripheral Tissue
LUO Lei1, ZHAO Yuan-li1, GE Xiang-hong1, ZHANG Xiao-dong1, HAO Zhi-fang2, Lü Jing3
1. School of Physical Engineering, Zhengzhou University, Zhengzhou 450052, China 2. Medicine College of Zhengzhou University, Zhengzhou 450052, China 3. Center Hospital of Zhengzhou, Zhengzhou 450052, China
Abstract：On the basis of some theories about fuzzing pattern recognition, the present article studied the data preprocessing of the Ramam spectrum of tumor peripheral tissue, and feature extraction and selection. According to these features the authors improved the leaning towards the bigger membership function of trapezoidal distribution. The authors built the membership function of Raman spectrum of tumor peripheral tissue which belongs to malignant tumor on the basis of 40 specimens, and designed the classifier. The test of other 40 specimens showed that the discrimination of malignant tumor is 82.4%, while that of beginning tumor is 73.9%.
Key words：Fuzzing pattern recognition;Adjacent averagant;Feature extraction and selection;PMBMF;Classifier
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