A Gaussian mixture autoregressive model for univariate time series. HECER discussion paper 352.Kalliovirta, L., M. Meitz, and P. Saikkonen (2015): "A Gaussian mixture au- toregressive model for univariate time series," Journal of Time Series Analysis, 36, 247-266....
最大期望算法(Expectation-maximization algorithm,又译为期望最大化算法),曾入选“数据挖掘十大算法”中,可见EM算法在机器学习、数据挖掘中的影响力。EM算法是最常见的隐变量估计方法,在机器学习中有极为广泛的用途,例如常被用来学习高斯混合模型(Gaussian mixture model,简称GMM)的参数。 EM算法是在概率模型中寻找参数...
GMM(Gaussian Mixture Model) 1.极大似然估计 http://blog.csdn.net/bingduanlbd/article/details/24384771 2.GMM概念: http://blog.csdn.net/abcjennifer/article/details/8198352 EM算法:http://www.cnblogs.com/jerrylead/archive/2011/04/06/2006936.html...
fromsklearn.mixtureimportGaussianMixtureimportnumpyasnp# 数据标准化defnormalize_data(data):return(data-np.mean(data,axis=0))/np.std(data,axis=0)data=np.random.rand(100,3)# 模拟数据data=normalize_data(data)# 实施GMMmodel=GaussianMixture(n_components=3,max_iter=100,random_state=42)model.fit(...
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Gaussian mixture model with feature selection: An embedded approach Computers & Industrial Engineering, Volume 152, 2021, Article 107000 YinlinFu, …,TeresaWu The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Po...
本文就高斯混合模型(GMM,Gaussian Mixture Model)参数如何确立这个问题,详细讲解期望最大化(EM,Expectation Maximization)算法的实施过程。 单高斯分布模型GSM 多维变量X服从高斯分布时,它的概率密度函数PDF为: x是维度为d的列向量,u是模型期望,Σ是模型方差。在实际应用中u通常用样本均值来代替,Σ通常用样本方差来代...
The work in [24] combines signals from a microphone and a bone sensor using a Gaussian mixture model on the high-resolution log spectra of each sensor. Similarly, multi-modal inputs are combined in [25] using deep denoising autoencoders that reconstruct Mel-scale features fed to an ASR ...
Then, virtual samples under the multiple operating mode condition are generated by proposing a Gaussian mixture model based virtual sample generation (GMMVSG) method. Applications of GMMVSG on Tennessee Eastman benchmark process and an industrial hydrocracking process show significant improvement of ...
The distribution that generates a vector within HMM state j is a Gaussian Mixture Model (GMM):p(x|j)=∑i=1MjwjiN(x;μji,Σji).Table 1 shows the parameters of the probability density functions (pdfs) in an example system of this kind: each context-dependent state (of which we only ...