现有平滑技术利用不同的折扣和补偿策略来处理数据稀疏问题，在计算复杂性与合理性方面各有其优缺点。
The present smoothing techniques deal with the data sparse problem using different discount and compensate strategy, and they have different merit or shortcoming on complexity and rationality.
现有平滑技术虽然已有效地对数据稀疏问题进行了处理，但对已出现事件频率分布的合理性并没有作出有效的分析。
The present smoothing techniques have solved the data sparse problem effectively but have not further analyzed the reasonableness for the frequency distribution of events occurring.
本文对交叉证认技术选取平滑因子的若干问题进行了探讨，许采用模拟数据的方式验证了作者的观点。
In this paper, some problems about smoothing factor selected by cross-validation technique are discussed and tested by using the simulation data.
通过补全缺失数据、平滑噪声数据、消除不一致数据等技术，得到高质量的数据。
Filling missing values, smoothing noise data and removing inconsistent data were all adopted to get high quality data.
应用小波变换对腹部MRI进行图像压缩与平滑化处理，应用边缘检测技术进行边缘数据与肝脏特征值的提取，并结合医师确定的肝脏区域进行图像分割效果的评价。
Wavelet transforms are used to compress image and smooth edge of liver region from abdomen MRI. The results of image segmentation are evaluated based on the liver region determined by doctor.
应用小波变换对腹部MRI进行图像压缩与平滑化处理，应用边缘检测技术进行边缘数据与肝脏特征值的提取，并结合医师确定的肝脏区域进行图像分割效果的评价。
Wavelet transforms are used to compress image and smooth edge of liver region from abdomen MRI. The results of image segmentation are evaluated based on the liver region determined by doctor.
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