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/458488/7295943
m addmult.m
function [s,p] = addmult(x,y)
% addmult Compute sum and product of two matrices
s = x+y;
p = x*y;
www.eeworm.com/read/458488/7295954
m twosum.m
function twosum(x,y)
% twosum Add two matrices and print the result
x+y
www.eeworm.com/read/450608/7480095
m gauss.m
%GAUSS Generation of a multivariate Gaussian dataset
%
% A = GAUSS(N,U,G,LABTYPE)
%
% INPUT
% N Array of number of objects to generate for each class
% U Dataset with means, labels a
www.eeworm.com/read/450608/7480385
m nbayesc.m
%NBAYESC Bayes Classifier for given normal densities
%
% W = NBAYESC(U,G)
%
% INPUT
% U Dataset of means of classes
% G Covariance matrices (optional; default: identity matrices)
%
% OUTP
www.eeworm.com/read/450608/7480395
m meancov.m
%MEANCOV Estimation of the means and covariances from multiclass data
%
% [U,G] = MEANCOV(A,N)
%
% INPUT
% A Dataset
% N Normalization to use for calculating covariances: by M, the number
%
www.eeworm.com/read/441245/7672650
m gauss.m
%GAUSS Generation of a multivariate Gaussian dataset
%
% A = GAUSS(N,U,G,LABTYPE)
%
% INPUT (in case of generation a 1-class dataset in K dimensions)
% N Number of objects to be generated (d
www.eeworm.com/read/441245/7673016
m nbayesc.m
%NBAYESC Bayes Classifier for given normal densities
%
% W = NBAYESC(U,G)
%
% INPUT
% U Dataset of means of classes
% G Covariance matrices (optional; default: identity matrices)
%
% OUTP
www.eeworm.com/read/197980/7959142
m joint_diag_r.m
function [ V , qDs ]= rjd(A,threshold)
%***************************************
% joint diagonalization (possibly
% approximate) of REAL matrices.
%***************************************
% This func
www.eeworm.com/read/144399/12796889
m addmult.m
function [s,p] = addmult(x,y)
% addmult Compute sum and product of two matrices
s = x+y;
p = x*y;
www.eeworm.com/read/144399/12796923
m twosum.m
function twosum(x,y)
% twosum Add two matrices and print the result
x+y