提出了基于最大互信息熵且具有奇数约束的优化得分函数。
A score function for optimization based on maximum mutual information entropy with odditional restriction is proposed.
最大互信息估计用于连接数字语音识别，识别率得到了提高。
The recognition rate is increased when maximum mutual information estimation is applied into connected digit speech recognition.
给出了一种基于最大互信息和边缘互方差的医学图像配准算法。
Gives a new algorithm of medical image registration based on maximum of mutual information and edge correlative deviation.
将最大互信息理论用于语音识别，最大互信息估计作为目标函数。
The theory of maximum mutual information is applied into speech recognition , maxi- mum mutual information estimation is used as object function .
本文在理论和试验分析的基础上得出结论该方法优于最大互信息法。
After theoretical and experimental analyses we draw a conclusion it's a better method than MMI in multi-modality image registration.
针对基于最大互信息的图像配准的不足，研究了基于角点的多光谱图像配准。
Due to the inferiority of image registration using maximum mutual information, we researched the registration based on corner points.
方法采用最大互信息法对6例患者PET和MRI三维脑图像进行刚体配准。
Methods Maximization of mutual information method was used in the rigid registration for PET and MRI images of 6 patients.
近年来基于最大互信息法的多模医学图象配准已成为医学图象处理领域的热点。
In these years, multimodality medical image registration based on maximization of mutual information has been popular in medical image processing fields.
本文基于多分辨分析策略，提出了以图像最大互信息为匹配测度的粒子群优化算法。
The main idea of the new method is to combine PSO algorithm with wavelet multiresolution strategy and parameters of PSO are adapted along with the resolution of the images.
本文研究了基于最大互信息和图象梯度组合的人脑CT与MRI多模医学图象配准算法。
This paper aims to research registration of CT and MRI images of caput based on gradient and normalized maximization mutual information method.
经典的最大互信息方法利用图像像素或体素灰度的统计特性很好地实现了配准的目的，使配准结果达到亚像素级；
The standard MMI method makes use of the statistical property of image voxels and pixels and arrives perfect results of registration, up to sub-voxel level.
我们现在定义这个信道的（信息）容量的最大互信息的输入和输出之间的所有分布满足的输入能力（大小）约束。
We now define the (information) capacity of the channel as the maximum of the mutual information between the input and output over all distributions on the input that satisfy the power constraint.
MEFS在基于最大熵原理的基础上，运用互信息和Z -测试技术，采用两步方法进行空间特征选择。
Based on the theory of maximum entropy, MEFS USES mutual information and Z-test technologies, and takes two-step method to execute feature selection.
MEFS在基于最大熵原理的基础上，运用互信息和Z -测试技术，采用两步方法进行空间特征选择。
Based on the theory of maximum entropy, MEFS USES mutual information and Z-test technologies, and takes two-step method to execute feature selection.
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