代码搜索：sparse
找到约 3,324 项符合「sparse」的源代码
代码结果 3,324
www.eeworm.com/read/331448/12827356
m som_neighbors.m
function Ne = som_neighbors(sM,neigh)
% Ne = som_neighbors(sM,neigh)
%
% sM (struct) map or data struct
% (matrix) data matrix, size n x dim
% [neigh] (string) 'kNN' or 'Nk' (which is va
www.eeworm.com/read/244790/12843628
m som_neighbors.m
function Ne = som_neighbors(sM,neigh)
% Ne = som_neighbors(sM,neigh)
%
% sM (struct) map or data struct
% (matrix) data matrix, size n x dim
% [neigh] (string) 'kNN' or 'Nk' (which is va
www.eeworm.com/read/243217/12954861
m ex1419.m
%例14-19 稀疏矩阵函数应用
S=sparse(randn(100)>3)
nnz(S)
nzmax(S)
issparse(S)
spy(S) %显示结果如图14-2
www.eeworm.com/read/243217/12954872
m ex1420.m
%例14-20 nnz和nzmax区别
S=sparse(rand(100)>0.98);
nnz(S)
nzmax(S)
B=double(S);
SS=B*B;
nnz(SS)
nzmax(SS)
whos
www.eeworm.com/read/141739/12988566
m som_neighbors.m
function Ne = som_neighbors(sM,neigh)
% Ne = som_neighbors(sM,neigh)
%
% sM (struct) map or data struct
% (matrix) data matrix, size n x dim
% [neigh] (string) 'kNN' or 'Nk' (which is va
www.eeworm.com/read/241396/13147531
asv t_jacobian.asv
function t_jacobian(quiet)
%T_JACOBIAN Numerical tests of partial derivative code.
% MATPOWER
% $Id: t_jacobian.m,v 1.2 2004/08/23 20:59:46 ray Exp $
% by Ray Zimmerman, PSERC Cornell
% Copy
www.eeworm.com/read/241396/13147559
m t_jacobian.m
function t_jacobian(quiet)
%T_JACOBIAN Numerical tests of partial derivative code.
% MATPOWER
% $Id: t_jacobian.m,v 1.2 2004/08/23 20:59:46 ray Exp $
% by Ray Zimmerman, PSERC Cornell
% Copy
www.eeworm.com/read/241396/13147682
m grad_ccv.m
function [df, dg] = grad_ccv(x, baseMVA, bus, gen, gencost, branch, Ybus, Yf, Yt, V, ref, pv, pq, mpopt)
%GRAD_CCV Evaluates gradients of objective function & constraints for OPF.
% [df, dg] = grad
www.eeworm.com/read/138987/13197392
m t_jacobian.m
function t_jacobian(quiet)
%T_JACOBIAN Numerical tests of partial derivative code.
% MATPOWER
% $Id: t_jacobian.m,v 1.2 2004/08/23 20:59:46 ray Exp $
% by Ray Zimmerman, PSERC Cornell
% Copy
www.eeworm.com/read/138987/13197464
m grad_ccv.m
function [df, dg] = grad_ccv(x, baseMVA, bus, gen, gencost, branch, Ybus, Yf, Yt, V, ref, pv, pq, mpopt)
%GRAD_CCV Evaluates gradients of objective function & constraints for OPF.
% [df, dg] = grad