Presently T-wave alternans (TWA) has become a clinical index of non-invasive diagnosis for heart sudden death prediction, and detecting T-wave alternate accurately is particularly important. This paper introduces an a...Presently T-wave alternans (TWA) has become a clinical index of non-invasive diagnosis for heart sudden death prediction, and detecting T-wave alternate accurately is particularly important. This paper introduces an algorithm for detecting TWA using Poincare mapping method which is a technique for nonlinear dynamic systems to display periodic behavior. Sample series of beat to beat cycles were selected to prepare Poincare mapping method. Vector Angle Index (VAI), which is the mean of the difference between θi (the angle between the line connecting the i point to the origin and the X axis) and 45 degrees was used to present the presence or absence of TWA. The value of 0.9 rad ≤ VAI ≤ 1.03 rad is accepted as a level determinative for presence of TWA. VAI via Poincare mapping method (PM) is used for correlation analysis with T-wave alternans voltage (Vtwa) by way of the spectral method (SM). The cross-correlation coefficient between Vtwa and VAI is γ = 0.8601. The algorithm can identify the absence and presence of TWA accurately and provide idea for further study of TWA-PM.展开更多
该文使用近10 a 4个时相的江苏全省Landsat遥感影像,在数据预处理的基础上提取归一化植被指数、比值植被指数、土壤调节植被指数、增强型植被指数、大气阻抗植被指数等5种植被指数,并进行主成分分析。运用最大似然法、随机森林法和光谱...该文使用近10 a 4个时相的江苏全省Landsat遥感影像,在数据预处理的基础上提取归一化植被指数、比值植被指数、土壤调节植被指数、增强型植被指数、大气阻抗植被指数等5种植被指数,并进行主成分分析。运用最大似然法、随机森林法和光谱角填图法进行分类,结合小班数据,对各方法的分类结果进行精度评价。评价结果表明,光谱角填图分类法在杨树信息提取时精度更高,对杨树的区分精度也达到42.67%。展开更多
针对当前无人机航空影像阴影角度校正方法存在校正精度和召回率较低,导致无人机航空影像信息的利用价值降低的问题,本文提出了立体测绘型双翼无人机航空影像阴影角度校正方法。以无人机检测到的影像阴影边缘为基础点,计算航空影像色彩...针对当前无人机航空影像阴影角度校正方法存在校正精度和召回率较低,导致无人机航空影像信息的利用价值降低的问题,本文提出了立体测绘型双翼无人机航空影像阴影角度校正方法。以无人机检测到的影像阴影边缘为基础点,计算航空影像色彩空间的色调差参照值和阴影区域的色调分量,根据阴影区域的纹理特征,去除无人机航空影像的阴影;考虑双翼无人机航行的空间位置,将无人机航空影像的RGB(red green blue)色彩空间转换为HSV(hue saturation value)色彩空间,通过无人机航空影像阴影角度的平滑处理,控制无人机航空影像阴影角度;利用灰度线性变化算法与自适应阈值计算法,对无人机航空影像阴影角度进行校正处理,实现对无人机航空影像阴影角度的精确校正,完成无人机航空影像阴影角度的控制与校正算法设计。结果表明:采用本文方法在Txcet-M数据集和Nfteg-H数据集进行航空影像测试,校正精度最高可达99%,召回率最高为98%;在GIswu-K数据集进行测试,得到的校正精度和召回率均在75%以上。这说明利用本文方法可以较好地优化航空影像阴影角度校正性能。展开更多
文摘Presently T-wave alternans (TWA) has become a clinical index of non-invasive diagnosis for heart sudden death prediction, and detecting T-wave alternate accurately is particularly important. This paper introduces an algorithm for detecting TWA using Poincare mapping method which is a technique for nonlinear dynamic systems to display periodic behavior. Sample series of beat to beat cycles were selected to prepare Poincare mapping method. Vector Angle Index (VAI), which is the mean of the difference between θi (the angle between the line connecting the i point to the origin and the X axis) and 45 degrees was used to present the presence or absence of TWA. The value of 0.9 rad ≤ VAI ≤ 1.03 rad is accepted as a level determinative for presence of TWA. VAI via Poincare mapping method (PM) is used for correlation analysis with T-wave alternans voltage (Vtwa) by way of the spectral method (SM). The cross-correlation coefficient between Vtwa and VAI is γ = 0.8601. The algorithm can identify the absence and presence of TWA accurately and provide idea for further study of TWA-PM.
文摘该文使用近10 a 4个时相的江苏全省Landsat遥感影像,在数据预处理的基础上提取归一化植被指数、比值植被指数、土壤调节植被指数、增强型植被指数、大气阻抗植被指数等5种植被指数,并进行主成分分析。运用最大似然法、随机森林法和光谱角填图法进行分类,结合小班数据,对各方法的分类结果进行精度评价。评价结果表明,光谱角填图分类法在杨树信息提取时精度更高,对杨树的区分精度也达到42.67%。
文摘针对当前无人机航空影像阴影角度校正方法存在校正精度和召回率较低,导致无人机航空影像信息的利用价值降低的问题,本文提出了立体测绘型双翼无人机航空影像阴影角度校正方法。以无人机检测到的影像阴影边缘为基础点,计算航空影像色彩空间的色调差参照值和阴影区域的色调分量,根据阴影区域的纹理特征,去除无人机航空影像的阴影;考虑双翼无人机航行的空间位置,将无人机航空影像的RGB(red green blue)色彩空间转换为HSV(hue saturation value)色彩空间,通过无人机航空影像阴影角度的平滑处理,控制无人机航空影像阴影角度;利用灰度线性变化算法与自适应阈值计算法,对无人机航空影像阴影角度进行校正处理,实现对无人机航空影像阴影角度的精确校正,完成无人机航空影像阴影角度的控制与校正算法设计。结果表明:采用本文方法在Txcet-M数据集和Nfteg-H数据集进行航空影像测试,校正精度最高可达99%,召回率最高为98%;在GIswu-K数据集进行测试,得到的校正精度和召回率均在75%以上。这说明利用本文方法可以较好地优化航空影像阴影角度校正性能。
