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/493704/6389121
m alamouti.m
%Simulation parameters for the verson without GUI
N=100; %total number of symbol pairs to be transmitted (should be at least 10 times more than expected 1/min(BER))
M=2; %PSK order (must be a
www.eeworm.com/read/493734/6389716
m lsm.m
num=[1 6.5 14 11.5 3];
den=[1 20 120 232 320];
u=mseries(16);% to generate a signal of m series
[z,A,B]=getval(num,den); % to function as a way to get z,A,and B.
x1=length(A);% to get the length o
www.eeworm.com/read/493294/6399910
m ksvdd.m
%KSVDD Support Vector Data Description on general kernel matrix
%
% W = KSVDD(X,FRACERR,WK)
%
% Train an SVDD on the data X, which is first mapped by mapping WK
% (see for possibilities myproxm
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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/493294/6400011
m mog_p.m
function p = mog_P(x,covtype,means,invcovs,priors)
%MOG_P Compute the probability density of a Mixture of Gaussians
%
% P = MOG_P(X,COVTYPE,MEANS,INVCOVS,PRIORS)
%
% Calculate the probability de
www.eeworm.com/read/493294/6400278
m dlpdda.m
function W = dlpdda(x,nu,usematlab)
%DLPDDA Distance Linear Programming Data Description attracted by the Average distance
%
% W = DLPDDA(D,NU)
%
% This one-class classifier works directly on th