Pulse classification and recognition optimization based on fuzzy neural networks

被引:0
|
作者
Wang, Yan [1 ]
Cai, Ji-Fei [1 ]
Jiang, Ning-Ning [2 ]
机构
[1] Beijing Inst Graph Commun, Sch Mech Engn, Beijing 102600, Peoples R China
[2] Armed Police Headquarters Commun Stn, Beijing 100008, Peoples R China
关键词
The pulse research of traditional Chinese medicine; fuzzy recognition; fuzzy neural network; local evolution algorithm;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The human system is a complex time varying and nonlinear system, of which pulses are the output. In order to objectively and quantitatively identify and study pulse signals, a method combining artificial neural networks (ANN) and fuzzy theory was applied to classify and recognize pulse signals. Fuzzy neural networks (NN) were adopted to perform weight adjustments according to fuzzy reasoning rules, which improved the reliability and accuracy of the pulse classification results. The fuzzy NN learning algorithm was applied to the fuzzy reasoning process according to the new fuzzy reasoning rules of data extension, realizing the interaction between systems and environment and updating knowledge and optimization models. The algorithm also established the necessary foundation for pulse diagnostic expert systems to adapt and optimize.
引用
收藏
页码:804 / 812
页数:9
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