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用于高光谱图像处理的matlab程序，包括图像融合，降维和图像的极大似然分类程序-for hyperspectral image processing Matlab procedures, including image fusion, dimensionality reduction and image of the maximum likelihood classification procedures
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经典的最大似然法分类法的C语言实现，有助于深入了解遥感分类原理。-This program implements the maximum likelihood classification procedure. ouput:1.classified image, and 2. probability file.
Note: For constructong variance-covariance matrix must be generic binary file.
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This function calculate the performance, based on Bayes theorem, of a clinical test. The input is based on a 2x2 matrix (true positive, false positives false negative, true negatives).
The Outputs are:
- Prevalence of disease
- Test Sensibility
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Algorithms for QAM Signal Classification Using Maximum Likelihood Approach Based on the Joint Probability Densities of Phases and amplitudes
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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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针对MPSK信号的调制识别问题，本文提出了一种新的最大似然比调制分类算法，采用平均释然比检测方法，通过对接收信号的的离散化和对主要参数的简要近似，得到了离散情况下的近似分类统计量！-MPSK signals for modulation recognition problem, we propose a new maximum likelihood modulation classification algorithm, using an average of more than relieve
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人脸识别的稀疏表示识别方法将稀疏表示的保真度表示为余项的L2范数，但最大似然估计理论证明这样的假设要求余项服从高斯分布，实际中这样的分布可能并不成立，特别是当测试图像中存在噪声、遮挡和伪装等异常像素，这就导致传统的保真度表达式所构造的稀疏表示模型对上述这些情况缺少足够的鲁棒性。而最大似然稀疏表示识别模型则基于最大似然估计理论，将保真度表达式改写为余项的最大似然分布函数，并将最大似然问题转化为一个加权优化问题-Recently the sparse representation (or codin
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不错的GM_EM代码。用于聚类分析等方面。- GM_EM- fit a Gaussian mixture model to N points located in n-dimensional
space.
Note: This function requires the Statistical Toolbox and, if you wish to
plot (for k = 2), the function error_ellipse
Elem
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利用男女身高体重利用贝叶斯算法，最大似然估计，最小风险估计等进行性别分类判决-The use of male and female height and weight using Bayesian algorithm, maximum likelihood estimation, minimum risk estimation for gender classification ruling
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经典的最大似然法分类法的C语言实现，有助于深入了解遥感分类原理。-This program implements the maximum likelihood classification procedure. ouput:1.classified image, and 2. probability file.Note: For constructong variance-covariance matrix must be generic binary file.
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基于MATLAB的模式识别的参数估计的最大似然估计，处理水环境分类问题，共分为5类，最后利用贝叶斯决策得出五类总的识别率。
-Maximum likelihood estimation of parameters of pattern recognition of MATLAB estimation based on classification of water environment treatment problem, is divided into 5 categories, the
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实现简单的遥感图像分类处理,使用的语言为C++，其中监督分类为最大似然算法，非监督分类为ISODATA算法-Can achieve a simple remote sensing image classification, the language used is C++, which is the maximum likelihood supervised classification algorithms, unsupervised classification algorithm for
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In this paper we present Discriminative Random Fields (DRF), a discrim- inative framework for the classification of natural image regions by incor- porating neighborhood spatial dependencies in the labels as well as the observed data. The proposed mo
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用于高光谱图像处理的matlab程序，包括图像融合，降维和图像的极大似然分类程序-For hyperspectral image processing matlab procedures, including image fusion, image dimension reduction and maximum likelihood classification procedure
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Abstract—In slow frequency hopping systems, it is critical
to detect, classify, and mitigate interference, as it degrades the
system performance. Generalized likelihood ratio test algorithm
was proposed for the detection of interference. Howeve
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是路径规划的实用方法，最大似然（ML）准则和最大后验概率（MAP）准则，是信号处理的基础，光纤陀螺输出误差的allan方差分析，IDW距离反比加权方法，Relief计算分类权重。-Is a practical method of path planning, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Is the basis of the signal processing, allan
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现代信号处理中谱估计在matlab中的使用，相关分析过程的matlab方法，代码里有很完整的注释和解释，Relief计算分类权重，包括主成分分析、因子分析、贝叶斯分析，最大似然（ML）准则和最大后验概率（MAP）准则。-Modern signal processing used in the spectral estimation in matlab, Correlation analysis process matlab method, Code, there are very complet
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实现最大似然分类，一段用于学习的代码
也许会有用吧(Maximum likelihood classification)
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This code implements the max likelihood classification
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用于高光谱图像处理的matlab程序，包括图像融合，降维和图像的极大似然分类程序(Matlab program for hyperspectral image processing, including image fusion, dimension reduction, and maximum likelihood classification of images)
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