代码搜索:decomposition

找到约 1,689 项符合「decomposition」的源代码

代码结果 1,689
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h surfaceletfilterbank.h

////////////////////////////////////////////////////////////////////////// // SurfBox-C++ (c) ////////////////////////////////////////////////////////////////////////// // // Yue Lu and Minh N. Do
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cpp chodcm.cpp

void chodcm(double a[], int n, double d[], double t[]) { int i,j,k; double sum; for (i = 1; i
www.eeworm.com/read/402842/11527034

m frit.m

function [r, l, m] = frit(a, n, wname) % FRIT Finite ridgelet transform % [r, l, m] = frit(a, n, wname) % % Input: % a: image matrix of size P by P, P is a prime number % n: number of wavelet de
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m ifrito.m

function a = ifrito(r, l, m, wname) % IFRITO Inverse orthogonal finite ridgelet transform % a = ifrito(r, l, m, wname) % % Input: % r: ridgelet coefficients in a (P-1) by (P+1) matrix,
www.eeworm.com/read/402729/11528740

m wavecompression.m

% Wavelet image compression - RGB images clear all; close all; % Reading an image file im = input('Enter a image'); X=imread(im); % inputting the decomposition level and name of the wavelet n=
www.eeworm.com/read/262547/11586997

m io.m

function ort = io(x,imf) % ort = IO(x,imf) computes the index of orthogonality % % inputs : - x : analyzed signal % - imf : empirical mode decomposition lx = size(imf,2); n = size(imf,1
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m testwaveletkernel.m

% % this is a script for testing and looking into wavelet kernel % and different decompositions. % % clear all close all % this is the data N=50; x=linspace(0,1,N)'; % these are the
www.eeworm.com/read/262186/11602403

m createmultilevelkernel.m

function [K,Kt]=CreateMultiLevelKernel(xapp,xtest,kerneloption,level) % USAGE % % [K,Kt]=CreateMultiLevelKernel(xapp,xtest,kerneloption,level) % % This function creates multiscale kernels K an
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m waveletuse.m

function waveletuse(OpenPath,IN1,IN2,kind,nflag,n) %IN1--->'den',进行小波去噪运算 %IN1--->'cmp',进行小波压缩运算 %IN2 is 'wv' for wavelet or 'wp' for wavelet packet. %filepath--->数据文件所在路径(十进制的文本稳当数据文件(一维)或图象格式)
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m testwaveletkernel.m

% % this is a script for testing and looking into wavelet kernel % and different decompositions. % % clear all close all % this is the data N=50; x=linspace(0,1,N)'; % these are the