1) nonuniformity weight
非均匀权值
2) uniformity weight
均匀权值
3) nonuniform weight
非均匀权重
1.
We investigate the event weighting method in the measurement of the entropy on the data sample with nonuniform weight distributions.
研究了具有非均匀权重分布样本的系统熵的计算方法。
4) non-uniform weighting
非均匀加权
5) irregular interpolation
非均匀插值
1.
The traditional interpolation methods are effective in dealing with data on regular nodes, but in practical, the sample points are often irregular, because of the error caused by various aspects, such as motion blur, data loss and other reasons, therefore irregular interpolation has very practical significance.
传统的插值方法一般是针对均匀数据而言的,但在实际操作中,由于各方面的误差,如运动模糊,数据丢失等原因,样本点往往是不规则的,因此对非均匀插值算法的研究具有很重要的实际意义。
6) nonuniformly weighted patterns
非均匀加权组合
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