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Analysis of eight volume pulse elements based on the BP neural network

机译:基于BP神经网络的八个体积脉冲元素分析。

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To solve the problem of the low rate of recognition in current complex pulse recognition, this paper puts forward a new approach to it. The paper preprocess and analyze the pulse information by using the neural network and genetic algorithm. The algorithm system includes pulse information collecting, network training, simulant diagnosis, correlation analysis. Pearson's coefficient test shows the system is of high reliability and testing accuracy. This system is more effective to solve the problem of pulse elements recognition. The method that making collection analysis between waveform and finger sense factor will be helpful for further research on the formation mechanism.
机译:为解决当前复杂脉冲识别中识别率低的问题,提出了一种新的方法。本文利用神经网络和遗传算法对脉冲信息进行预处理和分析。该算法系统包括脉搏信息采集,网络训练,模拟诊断,相关分析。皮尔逊系数测试表明该系统具有很高的可靠性和测试精度。该系统更有效地解决了脉冲元素识别的问题。在波形和手指感测因素之间进行收集分析的方法将有助于进一步研究其形成机理。

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