Search - gaussian fit

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[Other resource] MultivariateGaussianMixtureModelOptimizationbyCros DL : 0: Fit a multivariate gaussian mixture by a cross-entropy method. Cross-Entropy is a powerfull tool to achieve stochastic multi-extremum optimization.
Update : 2008-10-13 Size : 378.7kb Publisher : 阳关
[Other] gg DL : 0: 一个自已写的，很多data用一个gaussian distribution 去fit。
Update : 2008-10-13 Size : 1.66kb Publisher : 博邻
[matlab] MultivariateGaussianMixtureModelOptimizationbyCros DL : 0: Fit a multivariate gaussian mixture by a cross-entropy method. Cross-Entropy is a powerfull tool to achieve stochastic multi-extremum optimization.
Update : 2025-02-19 Size : 378kb Publisher : 阳关
[Industry research] High DL : 0: This paper presents a clustering approach which estimates the specific subspace and the intrinsic dimension of each class. Our approach adapts the Gaussian mixture model framework to high-dimensional data and estimates the parameters which best fit the data. We obtain a robust clustering method called High- Dimensional Data Clustering (HDDC). We apply HDDC to locate objects in natural images in a probabilistic framework. Experiments on a recently proposed database demonstrate the effectiveness of our clustering method for category localization.
Update : 2025-02-19 Size : 189kb Publisher : tra ba huy
[matlab] mmvn_toolkit DL : 0: A toolkit for Gaussian mixtures. flexible tools for: Generating univariate, multivariate, or mixtures of gaussians Interactive viewing tools allows viewing of multidimensional data and models. Initialize models, add and remove dimensions or clusters and inspect the fit in real-time. Also includes tools to subset the data using model-based (pseudo-)metrics.-A toolkit for Gaussian mixtures. flexible tools for: Generating univariate, multivariate, or mixtures of gaussians Interactive viewing tools allows viewing of multidimensional data and models. Initialize models, add and remove dimensions or clusters and inspect the fit in real-time. Also includes tools to subset the data using model-based (pseudo-)metrics.
Update : 2025-02-19 Size : 62kb Publisher : tra ba huy
[Program doc] Delineation DL : 0: This routine performs automatic curve fitting of overlapping lines. It uses a Levenberg-Marquardt fitting routine. The fit function can be Lorentzian, Gaussian or Mixed Lorentzian and Gaussian. Use Options->Line Fit to activate the line fitting procedure. First, one is asked to select a new block to hold the calculated lines. For example, if the spectrum is displayed in block 1, chose block 2 (must be a block with a higher number). -This routine performs automatic curve fitting of overlapping lines. It uses a Levenberg-Marquardt fitting routine. The fit function can be Lorentzian, Gaussian or Mixed Lorentzian and Gaussian. Use Options->Line Fit to activate the line fitting procedure. First, one is asked to select a new block to hold the calculated lines. For example, if the spectrum is displayed in block 1, chose block 2 (must be a block with a higher number).
Update : 2025-02-19 Size : 1.4mb Publisher : AMEL
[Algorithm] roughness DL : 0: 可以对一维波形数据进行拟合，高斯滤波，计算粗糙度等-Can be one-dimensional wave-shaped to fit the data, Gaussian filtering, calculation of roughness
Update : 2025-02-19 Size : 5kb Publisher : Mayf
[matlab] my_least_squares DL : 0: -least squares algorithms using gradient descent to find minimum of function - gaussian fit algorithm
Update : 2025-02-19 Size : 1kb Publisher : mic
[Graph program] gussian DL : 0: 高斯混合模型在图像处理方面运用广泛。她是利用已知的数学模型，通过逐渐逼近的方法，使得给定数据集和数据模型之间达成最佳拟合。-Gaussian mixture model widely used in image processing. She is the use of known mathematical models, through a gradual approximation approach that makes a given data set and the best fit between the data model.
Update : 2025-02-19 Size : 2kb Publisher : 赵晓霞
[matlab] Matlabsimulation DL : 0: 通过M atlab 模拟了随机产生的一定概率分布的信号序列, 叠加高斯噪声后利用最大后验概率(MAP)检测到的误码率, 做出BER~ SNR曲线, 并与理论计算得到的曲线进行比较, 两者吻合.-M atlab simulated by a certain probability distribution of random signal sequence, use of superposition of Gaussian noise is the maximum a posteriori (MAP) detection to the error rate, making BER ~ SNR curves obtained with the theoretical curve of the combined fit.
Update : 2025-02-19 Size : 99kb Publisher : qwq
[matlab] fit_mix_2D_gaussian DL : 0: fit_mix_2D_gaussian - fit parameters for a 2D mixed-gaussian distribution using EM algorithm format: [u,covar,t,iter] = fit_mix_2D_gaussian( X,M ) input: X - input samples, Nx2 vector M - number of gaussians which are assumed to compose the distribution output: u - fitted mean for each gaussian (each mean is a 2x1 vector) covar - fitted covariance for each gaussian. this is a 2x2xM matrix. t - probability of each gaussian in the complete distribution iter - number of iterations done by the function-fit_mix_2D_gaussian - fit parameters for a 2D mixed-gaussian distribution using EM algorithm format: [u,covar,t,iter] = fit_mix_2D_gaussian( X,M ) input: X - input samples, Nx2 vector M - number of gaussians which are assumed to compose the distribution output: u - fitted mean for each gaussian (each mean is a 2x1 vector) covar - fitted covariance for each gaussian. this is a 2x2xM matrix. t - probability of each gaussian in the complete distribution iter - number of iterations done by the function
Update : 2025-02-19 Size : 2kb Publisher : resident e
[matlab] fit_mix_gaussian DL : 0: fit_mix_gaussian - fit parameters for a mixed-gaussian distribution using EM algorithm format: [u,sig,t,iter] = fit_mix_gaussian( X,M ) input: X - input samples, Nx1 vector M - number of gaussians which are assumed to compose the distribution output: u - fitted mean for each gaussian sig - fitted standard deviation for each gaussian t - probability of each gaussian in the complete distribution iter- number of iterations done by the function- fit_mix_gaussian - fit parameters for a mixed-gaussian distribution using EM algorithm format: [u,sig,t,iter] = fit_mix_gaussian( X,M ) input: X - input samples, Nx1 vector M - number of gaussians which are assumed to compose the distribution output: u - fitted mean for each gaussian sig - fitted standard deviation for each gaussian t - probability of each gaussian in the complete distribution iter- number of iterations done by the function
Update : 2025-02-19 Size : 1kb Publisher : resident e
[matlab] 2dgaussian DL : 0: 汽车高斯曲面拟合 --- 2程序，以适应到表面二维高斯：子= A *的进出口（ -（（西为X0）^2/2/sigmax^2 +（艺Y0的）^2/2/sigmay^ 2）。。）+ b的这些例程是自动在某种意义上说，他们并不需要出发对模型参数的猜测规范。 autoGaussianSurfML（十一，彝，子）适合通过对模型参数的最大似然（最小二乘）。它首先计算了该模型在许多可能的参数值，然后选择最佳质量设置和细化与lsqcurvefit它。 autoGaussianSurfGS（十一，彝，紫）的估计，通过指定数据的贝叶斯生成模型，然后采取通过从模型吉布斯抽样样本后ofthis模型参数。这种-Auto Gaussian Surface fit --- 2 routines to fit a 2D Gaussian to a surface: zi = a*exp(-((xi-x0).^2/2/sigmax^2+ (yi-y0).^2/2/sigmay^2))+ b The routines are automatic in the sense that they do not require the specification of starting guesses for the model parameters. autoGaussianSurfML(xi,yi,zi) fits the model parameters through maximum likelihood(least-squares). It first evaluates the quality of the model at many possible values of the parameters then chooses the best set and refines it with lsqcurvefit. autoGaussianSurfGS(xi,yi,zi) estimates the model parameters by specifying a Bayesian generative model for the data, then taking samples from the posterior ofthis model through Gibbs sampling. This method is insensitive to local minimain posterior and gives meaningful error bars (Bayesian confidence intervals)
Update : 2025-02-19 Size : 7kb Publisher : zzskzcau
[matlab] q_Gaussian_fit DL : 0: Tsallis statistics-q Gaussian fit
Update : 2025-02-19 Size : 4kb Publisher : tekked
[Special Effects] 2dgaussian200 DL : 0: 2 functions to fit a 2D Gaussian or 2D Gabor to a surface. The routines are automatic in the sense that they do not require the specification of starting guesses for the model parameters.
Update : 2025-02-19 Size : 6kb Publisher : barbs
[AI-NN-PR] sumGaussFitting DL : 0: 数值算法，高斯和拟合，能够对输入的数据进行拟合，并且能够得出最佳的图形，非常值得下载。-Numerical algorithm, Gaussian, and fitting, to fit the input data, and can come to the best of the graphics, well worth the download.
Update : 2025-02-19 Size : 1kb Publisher : FSQ
[Special Effects] ellipse DL : 0: 从TEX文档中读取一系列点数据xy坐标，根据最小二乘原理，采用高斯全主元消去法来拟合椭圆曲线，求得椭圆基本参数。-From the TEX document to read a series of points xy coordinates, Gaussian full principal component elimination method based on the principle of least squares to fit the elliptic curve obtained the basic parameters of elliptical.
Update : 2025-02-19 Size : 3.71mb Publisher :
[matlab] fitgauss DL : 0: 一个matlab版本的高斯拟合程序，实现一维数组的高斯拟合-A version of Gaussian fitting matlab program to achieve a one-dimensional array of Gaussian fit
Update : 2025-02-19 Size : 2kb Publisher : liwenyi
[matlab] gaisinihe DL : 0: 用MATLAB实现高斯拟合函数-Gaussian fit function with MATLAB
Update : 2025-02-19 Size : 1kb Publisher : 苑康
[Other] Gaussian curve fitting DL : 0: 使用matlab进行曲线拟合，使用程序实现高斯(Gaussian)曲线拟合，而不使用cftool工具箱(guass surve fit, not use the cftool)
Update : 2025-02-19 Size : 3kb Publisher : Liu60

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