全部

1·A foundation for studying protein design using the HNP model and the relative entropy was made.

该工作为基于相对熵及HNP模型的蛋白质设计研究打下了基础。

2·Finally this paper point out application of relative entropy coefficient in pattern recognition.

最后指出了关联熵系数在模式识别中的应用。

3·Referring to the results of grey relation analysis, the results of relative entropy analysis is compared.

并参考灰关联分析结果，对相对熵分析结果进行比较。

4·A new contact intensity function is given to consist with protein design research based on the relative entropy.

为了与基于相对熵方法的蛋白质设计工作进行统一，采用了新的接触强度函数。

5·A algorithm of image segmentation is proposed based on relative entropy selection thresholding and edge detection.

利用相对熵选择阈值和边缘检测提出一种图象分割算法。

6·Experimental results show that the thresholding method based on relative entropy coefficient in this paper is feasible.

实验结果表明，本文提出的关联熵系数阈值分割方法是可行的。

7·The conception of relative entropy is put forward, and signification of the entropy conception in life science, is discussed.

提出了相对熵的概念，并讨论了熵概念在生命科学中的意义。

8·We numerically calculate the relative entropy of the entanglement and analyze in detail the linear entropy of the entanglement.

数值计算了相对熵纠缠度和计算分析了线性熵纠缠度。

9·Secondly, the weighted relative entropy was got by integrating relative entropy of multiple measures with weighted coefficients.

然后，通过加权系数融合多个测度相对熵而得到加权相对熵；

10·We propose a model-calibrated K-L relative entropy minimization (MKLEM) approach to using complete auxiliary information from survey data.

本文我们提出了使用调查数据中完全辅助信息的模型校正K-L相对熵最小化方法。