代码搜索：Solver
找到约 5,733 项符合「Solver」的源代码
代码结果 5,733
www.eeworm.com/read/466623/7029933
m examp6_5.m
mu=1000; x01=1; x02=2;
f=simget('c6mvdp'); % 首先获得默认的控制参数
f.Solver='ode15s'; % 选择仿真算法为 ode15s
[t,x,y]=sim('c6mvdp',[0,3000],f); % 在新选项下进行仿真
plot(t,y(:,1)), figure; plot(t,y(:,2))
www.eeworm.com/read/455033/7378676
edp lapcomplexeigenvalue.edp
// laplace with matrix
verbosity=1;
mesh Th=square(20,20,[pi*x,pi*y]);
fespace Vh(Th,P2);
Vh u1,u2;
Vh ur,ui;
int n=u1.n;
complex[int] Bu1(n),Bu2(n);
complex[int] Au1(n),Au2(n);
complex
www.eeworm.com/read/455033/7378717
edp lap_mat.edp
// laplace with matrix
verbosity=10;
mesh Th=square(10,10);
fespace Vh(Th,P1);
Vh u1,u2;
varf a(u1,u2)= int2d(Th)( dx(u1)*dx(u2) + dy(u1)*dy(u2) )
+ on(1
www.eeworm.com/read/455033/7379459
edp nsp1p2.edp
// remark: the sign of p is correct
bool classique=1;
cout > classique ;
real s0=clock();
mesh Th=square(10,10);
fespace Vh2(Th,P2);
fespace Vh(Th,P1);
fespace Wh(Th,[
www.eeworm.com/read/455033/7379460
edp aaa.edp
// remark: the sign of p is correct
bool classique=0;
real s0=clock();
mesh Th=square(10,10);
fespace Vh2(Th,P2);
fespace Vh(Th,P1);
fespace Wh(Th,[P2,P2,P1]);
Vh2 u2,v2,up1,up2;
Vh2 u1,v1;
Vh u1x
www.eeworm.com/read/441325/7671846
m have_fcn.m
function TorF = have_fcn(tag)
%HAVE_FCN Test for optional functionality.
% TorF = have_fcn(tag) returns 1 if the optional functionality is
% available, 0 otherwise.
%
% Possible values for inpu
www.eeworm.com/read/299459/7850274
c~ ssvm2_mex.c~
/*-----------------------------------------------------------------------
ssvm2_mex.c: MEX-file for single-class SVM with L2-soft margin.
Compile:
mex -O -I../../kernels -outdir ../ ssvm2_m
www.eeworm.com/read/299459/7850285
m~ bsvm2.m~
function [model]=msvm2( data, options )
% MSVM2 Multiclass SVM with 2-soft margin trained by single-class optimizer.
%
% Synopsis:
% model = mssvm( data, options)
%
% Description:
% This function i
www.eeworm.com/read/299459/7850401
m oaasvm.m
function model = oaasvm(data,options)
% OAASVM Multi-class SVM using One-Agains-All decomposition.
%
% Synopsis:
% model = oaasvm( data )
% model = oaasvm( data, options)
%
% Description:
% model