Decomposition

Implements the behaviours of the Decomposition Class. Provides methods for calculating matrix decomposition. usage:var inst:Decomposition = new Decomposition(max);

The Empirical Mode Decomposition is a technique to decompose a given signal into a set of elemental signals called Intrinsic Mode Functions. The Empirical Mode Decomposition is the base of the so-called d-deDUHilbert-Huang Transformd-deDt that comprises also a Hilbert Spectral Analysis and an...

This function plots the result of wavedec2 matlab function in two different modes. The first one called 'tree' displays all approximations and details coefficients (horizontal, vertical, diagonal), the second one called 'square' displays the classical "squared" representation of a wavelet image...


Platforms: Matlab

Quadtree decomposition of RGB image of size M-by-N-by-3. Three thresholds for red,green and blue components are used. For any R or G or B block if the maximum value of the block elements minus the minimum value of the block elements is greater than its respective threshold then the RGB block is...


Platforms: Matlab

It generates a stochastic field on a squared space. Samples are created by Latin hypercube sampling and the spatial correlation is performed by an algorithm based on Cholesky decomposition. Example inside.


Platforms: Matlab

This function does the decomposition of a separable nD kernel intoits 1D components, such that a convolution with each of thesecomponents yields the same result as a convolution with the full nDkernel, at a drastic reduction in computational cost.SYNTAX:======= [K1,KN,ERR] =...


Platforms: Matlab

This program will obtain the LU decomposition for any square matrix. The LU decomposition method consists of finding the L and U matrices that will satisfy the equation A=L*U, A being a square matrix.Once L and U found, in order to solve for x, we can rewrite the equation A*x=B as L*x_star=b...


Platforms: Matlab

Matrix decomposition using, e.g. the Cholesky decomposition requires the correlation matrix to be positive definite. That is, the eigenvalues must all be positive. In finance, this is rarely the case, and one often observes negative eigenvalues, or zero eigenvalues. These two functions do...


Platforms: Matlab

Graph::ModularDecomposition is a Perl module for modular decomposition of directed graphs. SYNOPSIS use Graph::ModularDecomposition qw(pairstring_to_graph tree_to_string); my $g = new Graph::ModularDecomposition; my $h = $g->pairstring_to_graph( ab,ac,bc ); print "yesn" if...


Platforms: *nix

GUI for univariate time series modeling and decomposition based on Pandit and Wu (1983)


Platforms: Matlab

This is the 2-D Fast DOST Decomposition. The computational complexity is O(NlnN)


Platforms: Matlab

Split the signal S(SPACE,TIME) into its downward/upward space propagating and stationnary components via a 2D Fourier decomposition. S is a (SPACE,TIME) matrix. We eventually proceed to a space and/or time filtering. DT,DX are temporal and space step. PERIOD=[Tmin Tmax] and WAVELENGTH=[Xmin Xmax]...


Platforms: Matlab

This scrip determines the column vector 'x', given the LU decomposition of matrix 'A'.It performs the forward substitution, finding 'y=L*z', then, by backward substitution: 'z=U*x', determines the values of 'x'.


Platforms: Matlab

The function is called upon as follows:a = bemd(im1);im1 -> Imagea(:,:,1) => IMF 1a(:,:,2) => IMF 2a(:,:,3) => IMF 3a(:,:,4) => Residu


Platforms: Matlab

This code was written to deal with "Zernike polynomials" code graciously donated by Paul Fricker via file exchange.Here you will find a practical example of a function decomposition byZernike basis.The function is F below, feel free to modifyUnlike Paul's example found in 'zernfun2.m' here the...


Platforms: Matlab

main executing reference usage: observeWaveletDecompositionBenchmark_N_levels.mThe objective is to illustrate wavelet decomposition, and to describe how operations may be done in the wavelet domain before the reconstruction. The demo decouples the wavelet operations (transform, operation in...


Platforms: Matlab

The solution of the nearest correlation matrix applies the hypershpere or spectral decomposition methods as outlined in Monte Carlo methods in Finance by Peter Jackel, Chapter 6.Use CorrelationExample.m that applies a simple example for the two cases.


Platforms: Matlab

The function qtdecomp_var.m peformes quad tree decomposition of square gray-scale image using varience criperion. If an image block has varience greater or equal to the whole image varience (optionally weighted), then the block is split further. The weighting has an effect on the splitting...


Platforms: Matlab

Using pyramid decomposition and iterative refinement, OF is calculated. Includes a demo and a paper that thoroughly explains the methodology.


Platforms: Matlab

rrlu computes a rank revealing LU factorization of a general m-by-n real full matrix A using partial pivoting with row and column interchanges.The factorization has the formA(P,Q) = L * Uwhere P and Q are permutation vectors, L is lower triangular(lower trapezoidal if m > n), and U is upper...


Platforms: Matlab