代码搜索：Matrix
找到约 10,000 项符合「Matrix」的源代码
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www.eeworm.com/read/402842/11527063
c fratc.c
/* Finite Radon Transform
*
* Author: Minh N. Do
*
* Version history:
* November 1999: First running version
* June 2000: Modified variable name to conform with the paper
* Changed the
www.eeworm.com/read/402842/11527065
c ifratc.c
/* Inverse Finite Radon Transform
*
* Author: Minh N. Do
*
* Version history:
* November 1999: First running version
* June 2000: Modified variable name to conform with the paper
* Cha
www.eeworm.com/read/402842/11527074
m fritm.m
function [r, l, m] = fritm(a, wname, maxR)
% FRITM Orthonormal finite ridgelet transform mixed with DCT
% [r, l, m] = fritm(a, wname, [maxR])
%
% Input:
% a: image matrix of size P by P, P is
www.eeworm.com/read/402842/11527084
m frat.m
function [r, m] = frat(f)
% FRAT Finite Radon Transform
%
% [r, m] = frat(f)
%
% Input:
% f: a P by P matrix. P is a prime.
%
% Output:
% r: a P by (P+1) matrix.
www.eeworm.com/read/402842/11527085
m fratf.m
function [y, m] = fratf(x)
% FRATF Finite Radon Transform
%
% [y, m] = fratf(x)
%
% Input:
% x: a P by P matrix. P is a prime.
%
% Output:
% y: a P by (P+1) matr
www.eeworm.com/read/400645/11571007
dat vmatrix2.dat
./vmatrix2
-------------------------------------------------------------------------------
Verify Advanced Operations on Matrices
---> Verify determinant evaluation
for a square matrix of size 20
www.eeworm.com/read/400577/11572679
m iscolumn.m
%ISCOLUMN Checks whether the argument is a column array
%
% [OK,Y] = ISCOLUMN(X)
%
% INPUT
% X Array: an array of entities such as numbers, strings or cells
%
% OUTPUT
% OK 1 if X is a column
www.eeworm.com/read/400577/11573021
m ldc.m
%LDC Linear Bayes Normal Classifier (BayesNormal_1)
%
% [W.R,S,M] = LDC(A,R,S,M)
% W = A*LDC([],R,S,M);
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/400577/11573030
m fisherm.m
%FISHERM Optimal discrimination linear mapping (Fisher mapping, LDA)
%
% W = FISHERM(A,N,ALF)
%
% INPUT
% A Dataset
% N Number of dimensions to map to, N < C, where C is the number of classes
www.eeworm.com/read/400577/11573192
m distm.m
%DISTM Compute square Euclidean distance matrix
%
% D = DISTM(A,B)
%
% INPUT
% A,B Datasets or matrices; B is optional, default B = A
%
% OUTPUT
% D Square Euclidean distance dataset or