To address the problem that dynamic wind turbine clutter(WTC)significantly degrades the performance of weather radar,a WTC mitigation algorithm using morphological component analysis(MCA)with group sparsity is studied...To address the problem that dynamic wind turbine clutter(WTC)significantly degrades the performance of weather radar,a WTC mitigation algorithm using morphological component analysis(MCA)with group sparsity is studied in this paper.The ground clutter is suppressed firstly to reduce the morphological compositions of radar echo.After that,the MCA algorithm is applied and the window used in the short-time Fourier transform(STFT)is optimized to lessen the spectrum leakage of WTC.Finally,the group sparsity structure of WTC in the STFT domain can be utilized to decrease the degrees of freedom in the solution,thus contributing to better estimation performance of weather signals.The effectiveness and feasibility of the proposed method are demonstrated by numerical simulations.展开更多
通过分析不同油茶砧木品种根系形态结构特征,为油茶砧木筛选和优化嫁接组合提供理论依据。本文选择了7个油茶砧木品种(‘XL82’‘GY12’‘GY13’‘GY14’‘EX4’‘8F-1’‘YX’),以油茶‘XL210’为接穗,测定不同砧穗组合油茶苗木的根总...通过分析不同油茶砧木品种根系形态结构特征,为油茶砧木筛选和优化嫁接组合提供理论依据。本文选择了7个油茶砧木品种(‘XL82’‘GY12’‘GY13’‘GY14’‘EX4’‘8F-1’‘YX’),以油茶‘XL210’为接穗,测定不同砧穗组合油茶苗木的根总长度、根表面积等9个根系性状指标,并运用相关分析、主成分分析和聚类分析等对砧木根系形态指标进行分析和综合评分。结果表明:不同砧穗组合油茶苗木的根系形态指标存在差异。‘EX4’的总根长、根表面积、根体积、连接数、节点数、根尖数和分叉数最大,分别为492.97 cm、117.17 cm 2、7.11 cm 3、1589.30个、1716.30个、985.00个、730.33个;‘8F-1’的分形维数最大,为1.55;‘XL82’的平均直径最大,为0.84 cm。细根(d≤2.00 mm)在总根系长度和根表面积中占比较高,‘GY12’在d≤2.00 mm径级根系长度和表面积中占比最高,‘8F-1’在d>5.00 mm径级根系长度、根表面积和根体积中占比最高。相关性分析表明,多个根系形态指标之间存在显著或极显著正相关(P<0.05或P<0.01)。主成分分析提取出2个主成分,累计贡献率达95.619%,‘EX4’综合得分最高。聚类分析将7个油茶砧木品种分为3类,‘EX4’根系形态指标值最高,‘GY12’‘8F-1’‘GY14’和‘YX’根系形态指标值中等,‘XL82’和‘GY13’形态指标值最低。聚类分析分类结果与主成分分析综合得分排名一致。‘EX4’砧木在根系形态结构特征方面表现优良,可作为油茶‘XL210’的优良砧木品种进行推广应用。展开更多
文摘To address the problem that dynamic wind turbine clutter(WTC)significantly degrades the performance of weather radar,a WTC mitigation algorithm using morphological component analysis(MCA)with group sparsity is studied in this paper.The ground clutter is suppressed firstly to reduce the morphological compositions of radar echo.After that,the MCA algorithm is applied and the window used in the short-time Fourier transform(STFT)is optimized to lessen the spectrum leakage of WTC.Finally,the group sparsity structure of WTC in the STFT domain can be utilized to decrease the degrees of freedom in the solution,thus contributing to better estimation performance of weather signals.The effectiveness and feasibility of the proposed method are demonstrated by numerical simulations.
文摘通过分析不同油茶砧木品种根系形态结构特征,为油茶砧木筛选和优化嫁接组合提供理论依据。本文选择了7个油茶砧木品种(‘XL82’‘GY12’‘GY13’‘GY14’‘EX4’‘8F-1’‘YX’),以油茶‘XL210’为接穗,测定不同砧穗组合油茶苗木的根总长度、根表面积等9个根系性状指标,并运用相关分析、主成分分析和聚类分析等对砧木根系形态指标进行分析和综合评分。结果表明:不同砧穗组合油茶苗木的根系形态指标存在差异。‘EX4’的总根长、根表面积、根体积、连接数、节点数、根尖数和分叉数最大,分别为492.97 cm、117.17 cm 2、7.11 cm 3、1589.30个、1716.30个、985.00个、730.33个;‘8F-1’的分形维数最大,为1.55;‘XL82’的平均直径最大,为0.84 cm。细根(d≤2.00 mm)在总根系长度和根表面积中占比较高,‘GY12’在d≤2.00 mm径级根系长度和表面积中占比最高,‘8F-1’在d>5.00 mm径级根系长度、根表面积和根体积中占比最高。相关性分析表明,多个根系形态指标之间存在显著或极显著正相关(P<0.05或P<0.01)。主成分分析提取出2个主成分,累计贡献率达95.619%,‘EX4’综合得分最高。聚类分析将7个油茶砧木品种分为3类,‘EX4’根系形态指标值最高,‘GY12’‘8F-1’‘GY14’和‘YX’根系形态指标值中等,‘XL82’和‘GY13’形态指标值最低。聚类分析分类结果与主成分分析综合得分排名一致。‘EX4’砧木在根系形态结构特征方面表现优良,可作为油茶‘XL210’的优良砧木品种进行推广应用。
基金国家自然科学基金No.61701388+13 种基金教育部归国留学人员科研扶持项目No.K05055陕西省自然科学基础研究计划项目No.2016JM60792016年碑林区科技计划项目No.GX1605陕西省教育厅专项No.17JK0431The National Natural Science Foundation of China under Grant No.61701388the Scientific Research Foundation for the Returned Overseas Chinese ScholarsState Education Ministry of China under Grant No.K05055the Natural Science Basic Research Plan of Shaanxi Province under Grant No.2016JM6079the Science and Technology Project of Beilin District in 2016 under Grant No.GX1605the Special Item of Shaanxi Provincial Department of Education under Grant No.17JK0431
文摘壁画数字化修复工作极大降低了手工修复时带来的不可逆的风险。根据唐墓室壁画人工修复时先整体结构、后局部纹理的思路,提出一种基于形态学成分分析(morphological component analysis,MCA)分解的唐墓室壁画修复算法。首先结合唐墓室壁画的特点,采用改进的MCA方法进行图像分解,得到结构部分和纹理部分;然后根据图像分解后纹理和结构的复杂程度与稀疏程度,分别采用简化的全变分(total variation,TV)算法和K奇异值分解(K-singular value decomposition,K-SVD)算法进行修复。实验结果表明,该算法可兼顾纹理与结构的修复效果,唐墓室壁画中的裂缝现象的破损修复精度得到提高。
