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Description: EM algorithm with a Rauch-Tung-Striebel smoother and an M step,内有说明-EM algorithm with a Rauch-Tung-Striebel's moother and an M step, which is described
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Size: 13312 |
Author: 大辉 |
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Description: 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。
-based on finite Gaussian mixture model of the EM algorithm source code, which has run reports and experimental results.
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Size: 52224 |
Author: 王 |
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Description: em算法matlab代码。解压缩后直接可以在matlab环境下运行-em algorithm Matlab code. Decompress directly in the operating environment Matlab
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Size: 5120 |
Author: 小咯 |
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Description: em算法求解混合高斯模型，适合图像处理中，对象分割-em algorithm Gaussian mixture model suitable for image processing, object segmentation
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Size: 1024 |
Author: 文刀 |
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Description: C语言版本的蚁群系统算法，详细介绍了蚁群算法的步骤-C language version of the ant system algorithm, introduced in detail the steps Ant Algorithm
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Size: 8192 |
Author: 葛荣雨 |
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Description: EM algorithm based on constrained mixture Gaussion model
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Size: 5120 |
Author: JAW |
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Description: EM算法，基于期望最大化原则进行密度估计-EM algorithm, based on the expectation maximization of the principle of density estimation
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Size: 3072 |
Author: 丁宏锴 |
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Description: 期望极大化（EM）算法及其应用，对从事统计研究的人比较游泳。-Expectation maximization (EM) algorithm and its application, to the conduct of statistical research compared to swimming.
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Size: 93184 |
Author: 胡兵 |
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Description: EM算法处理高斯混和模型，是用MATLAB实现的-EM algorithm for Gaussian mixture model of treatment is achieved using MATLAB
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Size: 1024 |
Author: 李晋博 |
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Description: 高斯分布期望优化（em）算法matlab实现，流量矩阵模型-Optimization of Gaussian distribution expectations (em) algorithm matlab realized, the flow matrix model
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Size: 3072 |
Author: jiangzhi |
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Description: 用matlab语言写的EM(Expectation maximization)算法,用于模式分类-Matlab language used to write the EM (Expectation maximization) algorithm for pattern classification
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Size: 2048 |
Author: 罗升阳 |
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Description: 本文提供了一个EM算法的指导性材料，很不错的，建议大家阅读一下-err
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Size: 98304 |
Author: guoguo |
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Description: 用EM算法进行图像的分割，matlab源代码。-EM algorithm using image segmentation, matlab source code.
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Size: 332800 |
Author: mona |
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Description: EM算法是机器学习领域中常用的一种算法，这个文件是EM算法最简单的一种实现，即在Gaussian Mixture model上面的EM。-EM field of machine learning algorithm is commonly used in an algorithm, this document is the most simple EM algorithm as a realization that, in Gaussian Mixture model above EM.
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Size: 3072 |
Author: De-Chuan Zhan |
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Description: 使用高斯模型期望值最大化演算法,做圖形分割
Gaumix_EM: EM Algorithm Applicated to Parameter Estimation for Gaussian Mixture
-Gaussian model using expectation maximization algorithm, to do graphics segmentation Gaumix_EM: EM Algorithm Applicated to Parameter Estimation for Gaussian Mixture
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Size: 1024 |
Author: 李致賢 |
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Description: In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
-In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar-xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
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Size: 197632 |
Author: 晨间 |
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Description: 高斯混合模型参数估计,EM算法,sunMOG.m为函数,testMOG4.m为测试程序-Gaussian mixture model parameter estimation, EM algorithm, sunMOG.m for the function, testMOG4.m for the test procedure
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Size: 1024 |
Author: junsun |
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Description: ％ EM algorithm for k multidimensional Gaussian mixture estimation
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％ Inputs:
％ X(n,d) - input data, n=number of observations, d=dimension of variable
％ k - maximum number of Gaussian components allowed
％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
％ maxiter - maximum number of iteration allowed ([] for none)
％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none)
％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none)
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％ Ouputs:
％ W(1,k) - estimated weights of GM
％ M(d,k) - estimated mean vectors of GM
％ V(d,d,k) - estimated covariance matrices of GM
％ L - log likelihood of estimates
％- EM algorithm for k multidimensional Gaussian mixture estimation Inputs: X (n, d)- input data, n = number of observations, d = dimension of variable k- maximum number of Gaussian components allowed ltol- percentage of the log likelihood difference between 2 iterations ([] for none) maxiter- maximum number of iteration allowed ([] for none) pflag- 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) Init- structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) Ouputs: W (1, k)- estimated weights of GM M (d, k)- estimated mean vectors of GM V (d, d, k)- estimated covariance matrices of GM L- log likelihood of estimates
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Size: 3072 |
Author: Shaoqing Yu |
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Description: 最近在做毕设，是有关高斯混合模型的算法，主要采用EM算法，这片硕士论文在这方面介绍的比较详细，可以去下载研究下。-Recently completed the set up to do, is the Gaussian mixture model algorithm, the main use of EM algorithm, this Master
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Size: 1801216 |
Author: |
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Description: 本算法包括最大似然估计，最小二乘估计，基于EM算法的多种混合高斯分布估计，EM算法测试实例，绘制每种分布的plot函数。非常有参考价值！-This algorithm, including maximum likelihood estimation, least squares estimation, based on the EM algorithm estimate a mixture Gaussian distribution, EM algorithm for the test examples, each mapping the distribution of the plot function. Very useful!
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Size: 22528 |
Author: liyuedsg |
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