代码搜索：M
找到约 10,000 项符合「M」的源代码
代码结果 10,000
www.eeworm.com/read/375515/2724159
m m5_3.m
%%%%%%%%% Gauss Quadrature %%%%%%%%%%%%%%
fprintf('Orders of the quadratures available are :n=2,3,4,5\n');
n=input('input n:');
while n>5|n==1
fprintf('\n warn: n=2,3,4,5\n');
n=input('
www.eeworm.com/read/375515/2724162
m m5_1.m
%%%%%%%%%%%%%%%% Trapezoidal or Simpson %%%%%%%%%%%%%%%%%%%%%%%%%%%
fprintf('\n Rules of Trapezoidal/Simpson\n');
fprintf('The function to be integrated is hard--coded infunction()\n');
z=input('
www.eeworm.com/read/373460/2761870
m~ m2osor.m~
function [model]=m2osor( data, labels, ker, arg, C, eps)
% M2OSOR Multi-class to one-class SVM translation and using SOR.
% [model]=m2osor( data, labels, ker, arg, C, eps)
%
% Inputs:
% data [dim x
www.eeworm.com/read/373460/2761882
m~ m2osmo.m~
function [model]=m2osmo( data, labels, ker, arg, C, eps, tol)
% M2OSMO Multi-class to one-class SVM translation and using SMO.
% [model]=m2osmo( data, labels, ker, arg, C, eps, tol)
%
% Use 'oaaclass
www.eeworm.com/read/373460/2761895
m m2osmo.m
function [model]=m2osmo( data, labels, ker, arg, C, eps, tol)
% M2OSMO One-Against-All multiclass SVM classifier using M-2-O
% transform and SMO.
% [model]=m2osmo( data, labels, ker, arg, C, eps, to
www.eeworm.com/read/373460/2761929
m m2osor.m
function [model]=m2osor( data, labels, ker, arg, C, eps)
% M2OSOR One-Against-All multiclass SVM classifier using M-2-O
% transform and SOR.
% [model]=m2osor( data, labels, ker, arg, C, eps)
%
% It
www.eeworm.com/read/259371/4344068
m4 cc-m.m4
# $Id: CC-M.m4,v 8.5 1999/05/27 22:03:28 peterh Exp $
depend: ${BEFORE} ${LINKS}
@mv Makefile Makefile.old
@sed -e '/^# Do not edit or remove this line or anything below it.$$/,$$d' < Makefile.ol
www.eeworm.com/read/472548/6869871
m m_odephas2.m
function status = m_odephas2(t,y,flag)
%ODEPHAS2 2-D phase plane ODE output function.
% When the string 'odephas2' is passed to an ODE solver as the 'OutputFcn'
% property, i.e. options = odese
www.eeworm.com/read/395356/8182334
m all_zone_m.m
function [Delta]=all_zone_m()
ps_location=evalin('base','ps_location');
beta=evalin('base','beta');
n=evalin('base','n');
M=evalin('base','M');
N=evalin('base','N');
ps=[ps_location,beta];
num=
www.eeworm.com/read/294886/8195671
m nnd12m.m
function nnd12m(cmd,arg1)
%NND12M Marquardt backpropagation demonstration.
%
% This demonstration requires the Neural Network Toolbox.
% First Version, 8-31-95.
%=============================