For many sample-based texture synthesis algorithms using markov random field model, the size of neighborhood determines the quality and speed of texture synthesis.

在许多采用马尔可夫随机场模型的基于样图的纹理合成算法中，邻域的大小决定着这些合成算法的纹理合成质量和合成速度。

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Binary response model choice is researched with the data of media or small sample size.

本文在中、小样本试验数据下，研究响应模型的选择问题。

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The paper discusses applying grey theory to power load forecasts, design equal-dimension and new-information model, and illustrate appropriate size of the sample on the basis of practical data.

文中将灰色理论应用于电力负荷预测，设计了等维新息模型，并根据实际数据说明了样本的合适长度。

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