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A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP-EM algorithm.
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统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含：
1，Analysis of linear discriminant function
2，Feature extraction: Linear Discriminant Analysis
3，Probability distribution estimation and clustering
4，Support Vector and other Kernel Machines,
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用高斯混合模型进行数据聚类分析的matlab 程序。,Set of files for analysis of Gaussian mixture models for data set clustering etc.
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GMM Gaussian Mixture Models in C
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a document about "Baseball Playfield Segmentation Using Adaptive Gaussian Mixture Models"
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very good Gaussian Mixture Models and Probabilistic Decision-Based Neural Networks for Pattern Classification - A Comparative Study document -very good Gaussian Mixture Models and Probabilistic Decision-Based Neural Networks for Pattern Classificatio
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EM算法（英文）A Gentle Tutorial of the EM Algorithm
and its Application to Parameter
Estimation for Gaussian Mixture and
Hidden Markov Models-A Gentle Tutorial of the EM Algorithm
and its Application to Parameter
Estimation for Gaussian Mixture a
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Gaussian Mixture Models (GMM) for speech noise reduction
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利用混合高斯模型进行前景检测的源代码实现，依据的是Stauffer发表的Adapptive background mixture models for real-time tracking.-The prospects for the use of Gaussian mixture model, detection of the source code implementation, based on the Stauffer published Adapptive background mix
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GMM Model Gaussian Mixture Models - Algorithm and
Matlab Code-GMM Model!
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Player Detection Algorithm Based on Gaussian Mixture Models Background Modeling
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Mixture of linear regressors. The routines contained in this file allow inference and learning of a mixture of linear-Gaussian regression models. Learning is performed by maximizing the data likelihood via the expectation maximization algorithm.
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《Software for Flexible Bayesian Modeling and Markov Chain Sampling》是机器学习领域专家Neal编写的用于Bayesian和马尔可夫链Linux下的C语言工具包。很有名，也很权威。
-This software supports Bayesian regression and classification models based on neural networks and Gaussian processes, and Ba
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用Matlab写的高斯混合模型的贝叶斯EM估计，-Variational Bayesian EM for Gaussian mixture models
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文章展示了基于高斯混合模型的语音频谱预测方法。频谱预测可能在传包过程中预防丢包这方面起到大作用。期望最大化算法用两倍或三倍的连续语音因素来测试模型。模型被用来设计第一，儿等指令预测量。预测表用频谱分配状态来估计并和一个简单的参考模型对比。最好的预测表得到一个平均频率扭曲值是0.46dB小于参考模型-This paper presents methods for speech spectrum prediction based
on Gaussian mixture models. Spec
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金融数据分析的一个新的程序码 可应用于数据分析 价格以及期货指数估计 还可用于 几何布朗运动的模拟-"An estimation technique for Time Indexed gaussian Mixture Models", we propose a model specification that can be used to describe data with spikes, jumps, mean reversion, geometric brownian motion, yo
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基于高斯混合模型，经由一种高效率的EM-MAP算法，解决图像超分辨率重建问题-A general framework for solving image inverse problems is introduced in this paper. The approach is
based on Gaussian mixture models, estimated via a computationally efficient MAP-EM algorithm.
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Matlab programs for gaussian mixture models
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This introduction to the expectation–maximization (EM) algorithm
provides an intuitive and mathematically rigorous understanding of
EM. Two of the most popular applications of EM are described in
detail: estimating Gaussian mixture models (GMMs),
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This collection of MATLAB files perform operations on Gaussian mixture models (GMMs) and Gaussian kernels (ie, Parzen windows). These utilities do evaluation, sampling, multiplication, convolution, linear transformation, mixture reduction, etc. Prese
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