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- Based on finite Gaussian mixture model of the EM algorithm source code, which has run reports and experimental results. 详细说明:基于有限高斯混合模型的EM算法的源程序代码,里面有实验报告和运行结果。
- We then describe an entropy penalized AMS learning algorithm on Gaussian mixture. 然后，我们描述了另一种基于熵惩罚的自动模型选择学习算法。
- In the current paper, we survey some main results of AMS on Gaussian mixture or general finite mixture. 本文将对于高斯混合模型或一般有限混合体模型的自动模型选择学习算法及其典型应用进行综述与总结。
- Then, built the color model for background and foreground utilizing the GMM (Gaussian mixture model). 然后利用高斯混合模型建立其前景和背景区域的颜色模型；
- We use the fixed-arithmetician DSP chip (chipboard) in the DSP, the algorithm of recognition is Gaussian mixture model. DSP方面使用的是定点运算的DSP板，而辨识的演算法是利用高斯混合模型。
- The former models skin regions with Gaussian mixture model (GMM) and sets up rules for skin detection. 针对GMM中分量数合理选择问题,提出一种基于聚类有效性函数的最优分量数确定方法,以提高肤色检测的精度。
- The author proposes a textured image segmentation algorithm which is based on multiresolution wavelet and Gaussian mixture models. 提出了一个基于多分辨率小波采样和高斯混合模型的纹理图像分割方法。
- For the two-component Gaussian mixture, it is hard to work out the maximum likelihood estimates (MLEs) and hence difficulty in the influence analysis. 摘要对于两高斯混合分布，很难求参数的极大似然估计，当然也不便于影响分析。
- Jeff A. Bilmes, “A Gentle Tutorial of EM Algorithm and its Application Parameter Estimation for Gaussian Mixture and Hidden Markov Models”. 郑顺德;“不特定语句中量语者辨识系统之设计研究;”国立中山大学电机工程研究所硕士论文;民国91年9月13日.
- Gaussian mixture model(GMM) has been widely used for text-independent speaker recognition.This method has simple and efficient character. 高斯混合模型(GMM)已广泛地应用于文本无关的说话人识别系统,该方法具有简单高效的特点。
- This dissertation adopts ASR based on Gaussian Mixture Model (GMM), so re-search emphasizes on robust features and speech enhancement techniques. 消除噪声所带来的失配可以映射到信号空间、特征空间和模型空间。
- Gaussian mixture model (GMM) is first trained for grass pixel, the grass distribution is then computed based on the trained GMM. 首先利用高斯混合模型(GMM)对草地颜色建模，然后利用已建立的GMM计算出每个镜头的草地颜色分布特征。
- All of those lower resultant image and original image are integrated to a feature vector of a pixel. Those pixels are segmented by Gaussian mixture models. 分解后的小波系数和图像共同组成了相应像素的特征向量,然后利用高斯混合模型进行分割。
- A neural network model based on Gaussian Mixture Models has been devised by Dirk Husmeier in 1997 in order to predict the conditional probability densities. Dirk Husmeier于1997年设计了一个基于高斯混合模型(简称GM模型)的神经网络用来预测概率密度。
- Introduce a novel feature selection algorithm based on Gaussian mixture model and do clustering on synthetic and real data making use of the results of the algorithm. 摘要介绍了一种新颖的基于高斯混合模型的特征选择算法，并且应用该方法的结果对模拟数据和真实数据进行聚类。
- The experimental results show that the proposed model can effectively cope with the inaccurate updating problem in the Gaussian mixture model due to the fixed update rate. 实验结果表明，该模型能较好地处理混合高斯模型因采用同一更新速率导致的背景模型更新错误问题。
- The traditional training methods of Gaussian Mixture Model(GMM) are sensitive to the initial model parameters,which often leads to a local optimal parameter in practice. 为了解决传统高斯混合模型(GMM)对初值敏感,在实际训练中极易得到局部最优参数的问题,提出了一种采用微粒群算法优化GMM参数的新方法。
- However,when the input noise is the double-peak Gaussian mixture noise,the noise can improve the signal correlation for the subthreshold signal and the suprathreshold signal,(i. 而当输入噪声为双峰高斯混合噪声时,不仅输入信号在阈下时随机谐振现象有时存在,而且输入信号在阈上时噪声往往也能改善信号的相关性,即阈上随机谐振现象存在。
- In this paper, a speaker identification system is proposed based on classify Fea-ture Sub-space Gaussian Mixture Model and Neural Net fusion (FS-GMM/NN) . 该文提出了一种基于分类高斯混合模型和神经网络融合(FS-GMM/NN)的说话人识别方法，通过对特征矢量进行聚类分析，将说话人的训练语音分成若干类。
- This paper discusses mainly the track association problem for multitarget tracking system.A novel algorithm of track correlation based on Gaussian mixture models is proposed. 摘要文中引入了高斯混合模型的概念，根据其统计特性，针对边扫描边跟踪雷达中的多目标跟踪问题，提出了一种新的判断航迹相关的算法。
