代码搜索：Matrix
找到约 10,000 项符合「Matrix」的源代码
代码结果 10,000
www.eeworm.com/read/418911/10891994
m blur.m
function [A,b,x] = blur(N,band,sigma)
%BLUR Test problem: digital image deblurring.
%
% function [A,b,x] = blur(N,band,sigma)
%
% The matrix A is an N*N-by-N*N symmetric, doubly block Toeplitz matrix
www.eeworm.com/read/418838/10894703
h decodeutil.h
#include
#include
#include
#include
int *ivector(int ilow,int ihigh);
int **imatrix(int ilow,int ihigh,int jlow,int jhigh);
double *vector(int ilow,i
www.eeworm.com/read/273787/10901165
m firbfb.m
% FIRBFB --- Biorthogonal Maximally decimation FIR Filter Bank
% Computation(1D)
% y = firbfb(x,A,T,M)
% x, y are input and output respectively. A is N1-by-M matrix;
% whose columns
www.eeworm.com/read/273787/10901180
m crsdiag.m
% A = crsdiag(M)
% Provide a cross diagnal matrix. The diagnal
% elements of the matrix will be 1,-1,1,-1 ...
function A = crsdiag(M)
for I = 1:M
a(I) = (-1)^(I-1);
end
A = diag(a);
www.eeworm.com/read/273533/10912526
cc shape.cc
/////////////////////////////////////////////////////////////
// Flash Plugin and Player
// Copyright (C) 1998,1999 Olivier Debon
//
// This program is free software; you can redistribute it and/or
/
www.eeworm.com/read/273409/10917115
cpp xt6-10.cpp
#include
using namespace std;
int main()
{void change(int *p);
int a[5][5],*p,i,j;
cout
www.eeworm.com/read/273093/10927667
m polyfit.m
function [p,S] = polyfit(x,y,n)
%p=polyfit(x,y,k)用k次多项式拟合向量数据(x,y)
%p返回多项式的降幂系数.当k>=n-1时,polyfit实现多项式插值.
%例如 用二次多项式拟合数据
% x | 0.1 0.2 0.15 0.0 -0.2 0.3
% --|-----------------------------
www.eeworm.com/read/418695/10935210
m distmaha.m
%DISTMAHA Mahalanobis distance
%
% D = distmaha(A,U,G)
%
% Computation of the Mahanalobis distances of all vectors in the
% dataset A to a dataset of points U, using the covariance matrix G.
% G
www.eeworm.com/read/418695/10935419
m gendatc.m
%GENDATC Generation of two circular classes with different
% variances
%
% A = gendatc(na,nb,k,ma)
%
% Generation of two sets of k dimensional Gaussian distributed data
% vectors. Class a has the
www.eeworm.com/read/418695/10935451
m gendatp.m
%GENDATP Parzen density data generation
%
% B = gendatp(A,m,s)
%
% Generation of m points using the Parzen estimate of the density of
% the dataset A using a smoothing parameter s. Default s or s