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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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针对智能交通系统中运动目标检测阶段存在的不足,提出了一种基于自适应混合高斯模型(GMM)的改进算法。-For the deficiencies of the intelligent transportation system moving target detection stage, an improved algorithm based on adaptive Gaussian mixture model (GMM).
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文章通过设计战场电视侦察系统的智能视频处理模块,提高了战场电视侦察系统的工作效率和智能化水平。首先
分析对重要军事目标进行监控的特点,归纳运动目标的特征,根据特征建立正常模型;然后运用中值滤波对监控视频进行
预处理,再采用基于高斯混合模型的背景减除法提取运动目标,通过特征提取确定运动目标的属性,与正常模型进行匹配
处理后,得出运动目标是否异常;最后达成敌重要目标有异常出现时自动告警的目的-Abstract:This article designs the intelligent vi
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混合高斯模型,前景检测,效果比较好,里边有运行的效果图片以及进行检测的视频-Gaussian mixture model, the prospect of testing, the results were quite good, running inside the effect of pictures and video test
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本文提供了利用高斯混合模型进行短时交通预测的算法描述,同时对于该算法的性能进行了评价。-This article provides a Gaussian mixture model for short-term traffic forecast algorithm descr iption, were evaluated for the performance of the algorithm.
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本代码主要实现的功能是基于高斯混合模型的运动目标检测。-This code is mainly the functions are based on gaussian mixture model of moving target detection.
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matlab上对于高斯混合模型的应用,对于图像做出处理的效果-For a Gaussian mixture model matlab on the application of the effect of the image to make a deal
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Continuous Birdsong Recognition Using Gaussian
Mixture Modeling of Image Shape Features
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opencv关于高斯混合模型的说明,可以应用在图像匹配等的领域,为图像处理提供很大方便。-Opencv on gaussian mixture model that can be applied in the field of image matching, etc, provides great convenience for image processing.
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程序展示了使用EM algorithm来训练GMM(Gaussian Mixture Model)来进行binary classification。-Program demonstrates the use of EM algorithm to train the GMM (Gaussian Mixture Model) for binary classification.
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针对扩展目标的高斯混合PHD滤波算法的论文-presents a Gaussian-mixture implementation
of the PHD filter for tracking extended targets
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GMM(高斯混合模型),在语音和图像方面有着广泛的作用,用于特征值的建模以及识别。-GMM (Gaussian mixture model), the voice and image has a broader role for the eigenvalues of modeling and identification.
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vs2010工程,C++(优化了opencv的代码),通过混合高斯背景建模实现的运动物体检测,效果非常好。-vs2010 project, C++ (optimized opencv code), Gaussian mixture background modeling to achieve through the detection of moving objects, the effect is very good.
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高斯混合模型的源代码。从文件中读取数据,用三个高斯混合模型进行处理-Gaussian mixture model of the source code. Read from the file data, using three Gaussian mixture model for processing
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基于混合高斯的运动目标检测的跟踪!修改后可以使用。-Gaussian mixture-based tracking of moving target detection! Modifications can be used.
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着重研究了基于高斯混合
模型(GMM, Gaussian Mixture Model)的运动目标检测算法
-Focuses on the Gaussian mixture model-based (GMM, Gaussian Mixture Model) of the moving target detection algorithm
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通过应用高斯混合模型来实现语音识别,语音样本为短时语音-By applying a Gaussian mixture model to achieve speech recognition, voice samples of short-time speech
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研究表明超高斯分布更加贴近语音信号的实际分布,然而语音信号很难用单一的概率密度
函数准确描述,针对这一情况,提出了一种用超高斯混合模型对语音信号幅度谱建模的新方法,并推导了
基于此模型的幅度谱最小均方误差估的估计式。仿真结果表明:与传统的短时谱估计算法相比,该算法不
仅能够进一步提高增强语音的信噪比,而且可以有效减小增强语音的失真度,提高增强语音的主观感知
质量。 -Recent research indicates that the speech spectral ampli
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传统的短时谱估计语音增强算法通常假设语音谱分量相互独立,没有考虑语音谱分量间的相关性。针对这
一问题,该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先,假设语音的离散余弦变换(DCT)
系数服从多元Laplace分布,以此利用谱分量间的相关性;在此基础上,利用多元随机矢量的高斯尺度混合模型表
示,推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式;并进一步推导了基于该分布模型的
语音存在概率,对最小均方误差估计子进行修正。实验结果表明,该算法
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Fast search for Dirichlet process mixture models -This code implements the search algorithms (modulo a few minor changes) described in the Fast search for DPMMs paper at AI-Stats 2007. It should work out of the box with a reasonably recent version of
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