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The authors present a targets detection method based on the hierarchical clustering which constructs the similarity measuring function according the movement rule of stars and targets,finds the optimal separating hyperplane and classified amount by means of finding the inflexion of error square sum function,then distinguish the targets from stars and noises by two level hierarchical clustering.

提出了基于层次聚类的空间弱小目标检测算法,以星点到参考恒星之间的距离变化为依据,根据恒星和目标的运动特性构造相似性度量函数,通过寻找误差平方和曲线拐点的方法寻找最优分类曲面和分类个数,最后以两层复合分类将恒星、噪声和目标分离。

We gain the distributing instance as a whole by the spatial analyse of the daily、 mensal and annual precipitation.Then, we adopt mean error、 mean absolute error、 mean relative error、 and the root mean squared interpolation error and the correlative coefficient as the determinant standard of interpolation effect. The results show that the mensal precipitation effect of SIA is the best, and the daily precipitation effect is worse reversely.

然后,对年降水量、月降水量以及日降水量的SIA结果采用平均误差、平均绝对误差、平均相对误差、插值平均误差平方和的平方根误差以及相关系数作为判定插值效果的标准,并得到以下结果:月降水量的SIA效果最好,日降水的相对较差。

In empirical study section, totally 40 agricultural listed companies were chosen as samples and 2002,2003,2004 as timeline studied and five variables of ownership concentration and three variables of ownership structure and two variables of controlling were defined. With the method of principal components the comprehensive variable of corporate performance was defined.

在实证分析部分,笔者以农林牧副渔类共40家上市公司为总样本,以2002年至2004年三个年度为考察期间,确定了股权集中度的五个指标(第一大股东持股比例、前五大股东持股比例的平方和、前五大股东持股比例之和、第一大股东和第二至第五大股东持股比例之和的差以及第一大股东与第二大股东持股比例的比值),股权构成的三个指标(国有股比例、法人股比例和流通A股比例),两个控制变量,采用主成分分析法确定了经营绩效的衡量指标,采用实证分析和规范分析相结合的方法,运用Eviews和SPSS统计软件,分析了我国农业上市公司的股权结构和经营绩效的关系。

It is a kind of itertive regularization method,and has the function adjusting regularization parameters automatically,so it overcomes the difficulties when solving the regularization parameters.

因此,对于这样的反问题,最后都可归结为极小化某些刻画问题的地质特征的测量值与理论计算值的误差平方和的函数的优化问题,约束条件为x≥0。

In order to correct the head motion in images.it was tried to find out some transformation parameters by calculating the minimum standard deviation between the reference image and the image being corrected.

本研究通过计算参考图像与被校图像之间残差平方和的极值找到移动变换参数,对手指运动磁共振脑功能成像中的头部移动进行校正

Used regression sum of squares to get the F-test statistic in order to test the random effect, the power of the test is increasing function of the test variance.

通过残差平方和构造了F检验统计量对是否有随机效应进行检验,并得出了检验的势函数是检验方差的增函数。

A high-performance modular exponentiation coprocessor, SEA, is presented here, and three novel ways are employed. First, a parallel binary modular exponentiation algorithm is used to decrease cycles, and a high radix Montgomery modular multiplication algorithm is modified to the radix based high radix Montgomery modular multiplication algorithm to increase the frequency; second when mapping algorithms to a systolic array, modular square and modular multiplication are alternatively computed to cover up the dependencies between iterations in the RBHRMMM algorithm and the bypass is used to eliminate the dependencies in the PBME algorithm; third, multipliers are split first, and then accumulations are compressed as partial products to decrease carry propagation delay in the critical path.

SEA是一种针对大数模幂的高性能协处理器,其主要采用如下3种加速方法:①采用二进位并行模幂算法和以基数长度为处理字长的高基数Montgomery算法;②将算法映射到脉动阵列处理结构,并交替计算平方和乘以掩盖RBHRMMM算法中的相关,同时应用定向技术消除PBME算法中的相关;③基於"先拆分乘法、后将累加压缩"的思想优化关键路径。

Gas emission;Partial regression square sum;Multiple regression

瓦斯涌出量;偏回归平方和;多元回归

The paper applies the theory of partial regression square sum into selecting the main prediction indexes which influence the gas emission in the coal mine. Based on these indexes, it constructs a multiple regression model to forecast gas emission.

将偏回归平方和理论运用到影响某矿瓦斯涌出量预测指标的选取中,确定了影响该矿瓦斯涌出量的主要影响因素,根据这些主要影响因素建立了预测瓦斯涌出量的多元回归模型。

Finally, it makes a discussion and draws a conclusion that the multiple regression model which is set up through selecting the complications of influencing gas emission with partial regression square sum parameter is feasible , at the same time, it plays a role in improving the accuracy of fitting prediction ,and it could be better for forecasting and controlling the gas emission in the coal mine.

最后,通过分析,得出结论:采用偏回归平方和参数对该矿瓦斯涌出量影响因素进行优选建立回归模型是可行的,同时有利于提高拟合精度,可以更好地对该矿瓦斯涌出量进行预报与控制。

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