Gaussian Calculationsd

Fit a multivariate gaussian mixture by a cross-entropy method. Cross-Entropy is a powerfull tool to achieve stochastic multi-extremum optimization.Please visit http://iew3.technion.ac.il/CE/ for more informationsi) Please compile mex-files by the mexme_ce_gauss.m (if compiler is not setup, run...

GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Expectation-Maximization (EM) iterative learning...

Free Split and Merge Expectation-Maximization algorithm for Multivariate Gaussian Mixtures. This algorithm is suitable to estimate mixture parameters and the number of conpounds Usage ------- [logl , M , S , P] = fsmem_mvgm(Z , [M0] , [S0] , [P0] , [option]); Inputs ------- Z Measurements (d x N)...


Platforms: Matlab

Generate Gaussian or Laplacian pyramids, or reconstruct an image from a pyramid. Contains a demo script doing image blending using pyramids. The function is more convenient to use than the Matlab function impyramid.


Platforms: Matlab

This code can be used to solve a set of linear equations using Gaussian elimination with partial pivoting. Note that the Augmented matrix rows are not directly switches. Instead a buffer vector is keeping track of the switches made. The final solution is determined using backward substitution.


Platforms: Matlab

em_ghmm : Expectation-Maximization algorithm for a HMM with Multivariate Gaussian measurement Usage ------- [logl , PI , A , M , S] = em_ghmm(Z , PI0 , A0 , M0 , S0 , [options]); Inputs ------- Z Measurements (m x K x n1 x ... x nl) PI0 Initial probabilities (d x 1) : Pr(x_1 = i) , i=1,...,d. PI0...


Platforms: Matlab

not getting results for 4 level/nlevel gaussian pyramid please try for improvement but gray levels are identified for successive levels and code is working wellunable to watch images for intermediate levels


Platforms: Matlab

This is a parallel implementation of the Expectation Maximization algorithm for multidimensional Gaussian Mixture Models, designed to run on NVidia graphics cards supportingCUDA. On my machine, it provides up to 170x performance increases (16 dims, 16 clusters, 1000000 data points).See the report...


Platforms: Matlab

Implementation details of (i)-(iii) can be found in [1].The fourth function (gmm2sv.m) is to concatenate the means (i.e. centers) of GMM. The concatenated mean of adapted GMM is known as GMM supervector (GSV) and it is used in GMM-SVM based speaker recognition system. Details of GMM-SVM based...


Platforms: Matlab

The code is explained in the article: Okunev, Pavel, "Fast Computation of the Economic Capital, the Value at Risk and the Greeks of a Loan Portfolio in the Gaussian Factor Model" (July 1, 2005). http://ssrn.com/abstract=758505 This implements one factor Gaussian model. [pd]=pdgs(L,w,p,LL,N) L =...


Platforms: Matlab

A fast generator of gaussian mixture samples with a general ND dimensional calling syntax.Permit to sample from a simple multivariate process to several gaussian mixture in a easy way.Please run mexme_sample_mvgm.m to compile on your own platform. (Be sure to mex -setup is done before)


Platforms: Matlab

HYPERGEOMETRIC2F1 Computes a hypergeometric function using the series expansion:f(a,b;c;x)=1 + [ab/1!c]x + [a(a+1)b(b+1)/2!c(c+1)]x^2 +[a(a+1)(a+2)b(b+1)(b+2)/3!c(c+1)(c+2)]x^3 + ...This function solves the Gaussian Hypergeometric Differential Equation:x(1-x)y'' + {c-(a+b+1)x}y' - aby = 0


Platforms: Matlab

The algorithm takes in a 1-D signal and finds the Gaussian derivative of it with the given kernel size and sigma, to provide the zero crossings. The zero crossings are then analyzed to give peaks and valleys. In order to remove very closely situated peaks and valleys, a width (provided by the...


Platforms: Matlab

MVG is a multivariate Gaussian (normal) random number generator. A user can generate a vector from the multivariate normal distribution of any dimension by specifying a mean vector and symmetric positive-definite covariance matrix. A linear transformation based on the Cholesky decomposition of...


Platforms: Matlab

At the moment, the Normal Inverse Gaussian (NIG) distribution is not included in the statistics toolbox. This collection of m-files supplements this toolbox with the most important functionalities for the NIG distribution: random numbers, moments, cdf, pdf and parameters by moment fit. This...


Platforms: Matlab

randgen(mu,mu1,mu2,cov1,cov2,cov3) = Random generation of Gaussian Samples in d-dimensions where d = 2mu, mu1, mu2 = (x,y) coordinates(means) that the gaussian samples are centered around. cov1, cov2, cov3 are the covariance matrices and will vary changing the shape of the distribution, example:...


Platforms: Matlab

Generates complex generalized gaussian random variables with augmentedcovariance matrix Ta = [2*s 0; 0 2*s];and shape parameter c, where c = 1 corresponds to the Gaussian case.x = cggd_rand(c,s,N) generates a vector 1xN of complex samples with a circulargaussian distribution with shape parameter...


Platforms: Matlab

This function plots a Gaussian impulse response, unit impulse and the% convolution/deconvolution of both using MATLAB's 'filter'. Specifically% it uses 'filter' rather than 'deconv' to do the deconvolution and thereby% returns the original Gaussian vector as well as the unit response vector.%...


Platforms: Matlab

Genereates random number from the closed-skew Gaussian distribution with two different methods:CSN_mcmc.mDoes mcmc, so each realisation are not completely independent% Usage: [res, t_wi, t_inv] =CSN_mcmc(Mu,Sigma,Gamma,Nu,Delta,num,burn)%% Mu,Sigma,Gamma,Nu,Delta: parameters in CSN% num: number...


Platforms: Matlab

Auto Gaussian & Gabor Surface fit---Functions to fit a 1D Gaussian to a curve and a 2D Gaussian or 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. This is done by evaluating the quality of fit for...


Platforms: Matlab