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作 者:QIN Jian LIU Hong-jian DENG Wei WU Guo-zhen CHEN Shu-qing JING Ming-hua
机构地区:[1]The first affiliated hospital, Sun Yat-Sen University, Guangzhou 510080, China
出 处:《Chinese Journal of Biomedical Engineering(English Edition)》2005年第3期114-119,共6页中国生物医学工程学报(英文版)
基 金:ThisitemissupportedbyNationalNaturalScienceFoundationofChina(No.30371717),StateAdministrationofTraditionalchi-neseMedicineofChina(No.02-03JP37),NaturalScienceFoundationofGuangdongProvince,china(No.031688).
摘 要:Based on the fuzzy characteristic of the pulse state and syndromes differentiation thinking mode of TCM, an information fusing recognition method of pulse states based on SFNN (Stochastic Fuzzy Neural Network) is presented in this paper. With the learning ability in parameters and structure, SFNN fuses the measurement information of three pulse-state sensors distributed in Cun, Guan, and Chi location of body for the pulse state recognition. The experimental results show that the percentage of correct recognition with new method is higher than that by single-data recognition one, with fewer off-line train numbers.Based on the fuzzy characteristic of the pulse state and syndromes differentiation thinking mode of TCM, an information fusing recognition method of pulse states based on SFNN (Stochastic Fuzzy Neural Network) is presented in this paper. With the learning ability in parameters and structure, SFNN fuses the measurement information of three pulse-state sensors distributed in Cun, Guan, and Chi location of body for the pulse state recognition. The experimental results show that the percentage of correct recognition with new method is higher than that by single-data recognition one, with fewer off-line train numbers.
关 键 词:Stochastic fuzzy neural network Information fusing Pulse state recognition
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