搜索资源列表
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6下载：
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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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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This code implements the search algorithms described in [1]. The code only contains the Dirichlet/Multinomial case, but the Gaussian case can be hacked in in about 5 minutes.
[1] Fast search for Dirichlet process mixture models Conference on AI
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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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解决了带有time index高斯混合模型的状态估计问题-An estimation technique for Time Indexed Gaussian Mixture Models
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DP Mixture Models实例程序，包含variational和Monte Carlo。-This is a matlab library for Gaussian Dirichlet Process Mixture Models (DPMMs).
It includes both variational and Monte Carlo inference.
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Demonstration of the reproduction of a generalized trajectory through Gaussian Mixture Regression (GMR), when considering two independent constraints represented separately in two Gaussian Mixture Models (GMMs). Through regression, a smooth generaliz
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Robert Gordon University的一个研究人员写的k-means聚类算法工具箱，内容完整可运行。-Includes k-means, hierarchical (single-, complete- and mean-linkage), EM for Gaussian Mixture Models, fuzzy c-means, and a demo.
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经典的em算法即期望最大化算法，可用于高斯混合GMM模型和聚类算法，-Classic em algorithm that expectation maximization algorithm can be used for Gaussian mixture models and GMM clustering algorithm,
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隐马尔科夫模型工具箱，readme文档介绍了该工具箱的使用方法-Hidden Markov Model (HMM) Toolbox written by Kevin Murphy (1998).
Seehttp://www.ai.mit.edu/~murphyk/Software/hmm.html for details.
Models
dhmm = HMM with discrete output
mhmm = HMM with mixture of G
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Suite of MATLAB based RFS filtering/tracking codes. The file contains single target filters thus Single target filter gms -Gaussian mixture solution for linear Gaussian models, ekf - EKF approximation for non-linear models
ukf -UKF approximatio
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一个EM算法 这是通过高斯混合模型进行聚类的EM算法的实现，使用图形在线表示。(EM algorithm
This is an implementation of the EM algorithm for Clustering via Gaussian mixture models, using graphical on-line representation.)
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