Gaussian Elimination Algorithm

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

The "GEE! It's Simple" package illustrates Gaussian elimination with partial pivoting, which produces a factorization of P*A into the product L*U where P is a permutation matrix, and L and U are lower and upper triangular, respectively.The functions in this package are accurate, but they are far... Platforms: Matlab

We focus on the lectures 20, 21, and 22 of the book "Numerical Linear Algebra" by Trefethen and Baum. Platforms: Matlab

Calculate pi using the Gaussian-Legendre algorithm. The function PIGL.M produces an ASCII file containing the number of decimals requested. The maximum number depends on free disk space and the RAM available. Platforms: Matlab

The conjugate gradient method aims to solve a system of linear equations, Ax=b, where A is symmetric, without calculation of the inverse of A. It only requires a very small amount of membory, hence is particularly suitable for large scale systems.It is faster than other approach such as Gaussian... Platforms: Matlab

Belief networks (also called Bayesian networks or causal networks) are a representation for independence amongst random variables for probabilistic reasoning under uncertainty. The purpose of this tool is to illustrate how probabilities are updated given new evidence in a belief network, and... Platforms: Mac

Magic Number Machine... A free, full-featured, graphically laid out, high-precision, scientific calculator for Mac OS X 10.4 or later. Full source-code is included with the distribution.Ideal if you need to enter large expressions or have accurate precision. "Data" drawers allow an easy way to... Platforms: Mac

The Linear Algebrator is a Mac OS X application for teaching or learning basic linear algebra, taking you step-by-step through both the Gauss-Jordan elimination algorithm for row reducing matrices as well as the Gram-Schmidt orthogonalization algorithm. You are free to perform row or column... Platforms: Mac

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

The Expectation-Maximization algorithm (EM) is widely used to find the parameters of a mixture of Gaussian probability density functions (pdfs) or briefly Gaussian components that fits the sample measurement vectors in maximum likelihood sense [1]. In our work, the expectation-maximization (EM)... 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

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

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

This is a function performs maximum likelihood estimation of Gaussian mixture model by using expectation maximization algorithm.It can work on data of arbitrary dimensions. Several techniques are applied in order to avoid the float number underflow problems that often occurs on applying... Platforms: Matlab

The Radial Basis Function (RBF) with LMS algorithm for Simulink.The Radial Basis Function (RBF)Batch-mode trainingFixed centers selected at randomThe Gaussian basis functionsComputing the output weights with LMS algorithmMarcelo Augusto Costa FernandesDCA - CT - UFRN Platforms: Matlab

Algorithm::Dependency is a base class for implementing various dependency trees. SYNOPSIS use Algorithm::Dependency; use Algorithm::Dependency::Source::File; # Load the data from a simple text file my $data_source = Algorithm::Dependency::Source::File->new( foo.txt ); # Create the... Platforms: *nix

Algorithm::Knapsack is a brute-force algorithm for the knapsack problem. SYNOPSIS use Algorithm::Knapsack; my $knapsack = Algorithm::Knapsack->new( capacity => $capacity, weights => @weights, ); $knapsack->compute(); foreach my $solution ($knapsack->solutions()) { foreach my $index... Platforms: *nix

Algorithm::DiffOld is a Perl module to compute `intelligent differences between two files / lists but use the old (<=0.59) interface. NOTE This has been provided as part of the Algorithm::Diff package by Ned Konz. This particular module is ONLY for people who HAVE to have the old interface,... Platforms: *nix

Algorithm::Loops is a Perl module with looping constructs: NestedLoops, MapCar*, Filter, and NextPermute*. SYNOPSYS use Algorithm::Loops qw( Filter MapCar MapCarU MapCarE MapCarMin NextPermute NextPermuteNum NestedLoops ); my @copy= Filter {tr/A-Z.,"()/a-z/d} @list; my $string= Filter... Platforms: *nix

Algorithm::Diff::Apply is a Perl module to apply one or more Algorithm::Diff diffs. SYNOPSIS ## Single-diff form: use Algorithm::Diff::Apply qw{apply_diff}; my @ary = ...; my @diff = ...; # some call to Algorithm::Diff::diff() my @changed_ary = apply_diff(@ary, @diff); my $changed_ary =... Platforms: *nix