代码搜索：Matrices
找到约 3,616 项符合「Matrices」的源代码
代码结果 3,616
www.eeworm.com/read/160391/5571623
m extract_params_from_gbn.m
function [B,D,mu] = extract_params_from_gbn(bnet)
% Extract all the local parameters of each Gaussian node, and collect them into global matrices.
% [B,D,mu] = extract_params_from_gbn(bnet)
%
% B(
www.eeworm.com/read/160391/5571706
m dbn_to_hmm.m
function [prior, transmat] = dbn_to_hmm(bnet)
% DBN_TO_HMM Compute the discrete HMM matrices from a simple DBN
% [prior, transmat] = dbn_to_hmm(bnet)
onodes = bnet.observed;
ss = length(bnet.int
www.eeworm.com/read/473584/6846743
c readmat.c
#include
#include
#include
#include
#include
#include "clustalw.h"
#include "matrices.h"
/*
* Prototypes
*/
static Boolean commentl
www.eeworm.com/read/195195/8168895
c readmat.c
#include
#include
#include
#include
#include
#include "clustalw.h"
#include "matrices.h"
/*
* Prototypes
*/
static Boolean commentl
www.eeworm.com/read/266642/11216428
m gschmidt.m
function [Q,R]=gschmidt(A,classic)
% ATLAST65中的施密特正交化子程序gschmidt
%
% The Gram-Schmidt QR factorization of a matrix A. If
% [Q R] = gschmidt(A), then Q and R are the matrices
% derived from the mo
www.eeworm.com/read/265447/11264116
html mod2dense.html
Dense Modulo-2 Matrix Routines
Dense Modulo-2 Matrix Routines
This module implements operations on matrices in which the elements
are all
www.eeworm.com/read/334951/12558798
dat matrx1.dat
MATRICES FOR INPUT TO TEST ROUTINES
Size of matrix (NxN), Number of solutions:
3 2
Matrix A:
1.0 0.0 0.0
0.0 2.0 0.0
0.0 0.0 3.0
Solution vectors:
1.0 0.0 0.0
1.0 1.0 1.0
NEXT PROBLEM
Size
www.eeworm.com/read/386050/8767329
m mds_stress.m
%MDS_STRESS - Sammon stress between dissimilarity matrices
%
% E = MDS_STRESS(q,Ds,D)
%
% INPUT
% q Indicator of the Sammon stress; q = -2,-1,0,1,2
% Ds Original distance matrix
% D App
www.eeworm.com/read/184067/9123821
m sort.m
%列状数据升序排列
%例如
% A=[11 4 0.2;22 3 0.5;0 3 0.4];
% sort(A)
%
%SORT Sort in ascending order.
% For vectors, SORT(X) sorts the elements of X in ascending order.
% For matrices, SORT(X)