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机构地区:[1]天津大学精密测试技术和仪器国家重点实验室 [2]天津电子信息职业技术学院,天津300072
出 处:《传感技术学报》2006年第3期724-727,749,共5页Chinese Journal of Sensors and Actuators
摘 要:通过相应法则提取曲线的特征极值,突出了曲线的特征位置,并且极大地压缩了待判曲线以及模板的数据量,提高了识别速度。结合归一化调整以及特征段幅度等算法,有效地克服噪声的干扰,准确识别待判曲线,具有较高的识别效率。实验结果证实了该方法的有效性和稳定性,识别率高,识别速度快,满足实时识别要求。The curve's characteristic extreme value is picked up through corresponding principle and accordingly, the characteristic position is highlighted. The data quantity of the curve and the template has been enormously compressed, hence the recognition speed has been improved. This kind of method combines the algorithm of unitary adjustment and characteristic range value, depressed the noise effectively, identify the curve accurately, and is of high recognition efficiency. According to the experimental result, this method has the character of high validity and stability, high discerning rate, and rapid recognition speed which can satisfies the real-time recognition request.
分 类 号:TP302[自动化与计算机技术—计算机系统结构]
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