| Information Fusing Recognition of Traditional Chinese Medicine （TCM） Pulse State Based on Stochastic Fuzzy Neural Network |
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| 引用本文： | QIN Jian LIU Hong-jian DENG Wei WU Guo-zhen CHEN Shu-qing JING Ming-hua. Information Fusing Recognition of Traditional Chinese Medicine （TCM） Pulse State Based on Stochastic Fuzzy Neural Network[J]. 中国生物医学工程学报(英文版), 2005, 14(3): 114-119 |
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| 作者姓名： | QIN Jian LIU Hong-jian DENG Wei WU Guo-zhen CHEN Shu-qing JING Ming-hua |
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| 作者单位： | The first affiliated hospital, Sun Yat-Sen University, Guangzhou 510080, China |
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| 基金项目： | This item is supported by National Natural Science Foundation of China（No. 30371717）,State Administration of Traditional chinese Medicine of China（No.02-03JP37）,Natural Science Foundation of Guangdong Province,china（No. 031688）. |
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| 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.
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Information Fusing Recognition of Traditional Chinese Medicine (TCM) Pulse State Based on Stochastic Fuzzy Neural Network |
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| QIN Jian,LIU Hong-jian,DENG Wei,WU Guo-zhen,CHEN Shu-qing,JING Ming-hua. Information Fusing Recognition of Traditional Chinese Medicine (TCM) Pulse State Based on Stochastic Fuzzy Neural Network[J]. Chinese Journal of Biomedical Engineering, 2005, 14(3): 114-119 |
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| Authors: | QIN Jian LIU Hong-jian DENG Wei WU Guo-zhen CHEN Shu-qing JING Ming-hua |
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| Abstract: | 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. |
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| Keywords: | Stochastic fuzzy neural network Information fusing Pulse state recognition |
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