代码搜索：gradient
找到约 2,951 项符合「gradient」的源代码
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www.eeworm.com/read/381423/2646630
entries
/collapse.gif/1.1/Sat Mar 10 05:53:52 2007/-kb/
/expand.gif/1.1/Sat Mar 10 05:53:52 2007/-kb/
/gradient-bg.gif/1.1/Sat Mar 10 05:53:52 2007/-kb/
/ns-collapse.gif/1.1/Sat Mar 10 09:32:21 2007/-kb/
www.eeworm.com/read/364803/2901261
entries
/collapse.gif/1.1/Sat Mar 10 05:53:54 2007/-kb/
/expand.gif/1.1/Sat Mar 10 05:53:54 2007/-kb/
/gradient-bg.gif/1.1/Sat Mar 10 05:53:54 2007/-kb/
/ns-collapse.gif/1.1/Sat Mar 10 05:53:54 2007/-kb/
www.eeworm.com/read/364803/2901309
entries
/collapse.gif/1.1/Sat Mar 10 05:53:53 2007/-kb/
/expand.gif/1.1/Sat Mar 10 05:53:53 2007/-kb/
/gradient-bg.gif/1.1/Sat Mar 10 05:53:53 2007/-kb/
/ns-collapse.gif/1.1/Sat Mar 10 05:53:53 2007/-kb/
www.eeworm.com/read/364803/2901420
entries
/collapse.gif/1.1/Sat Mar 10 05:53:52 2007/-kb/
/expand.gif/1.1/Sat Mar 10 05:53:52 2007/-kb/
/gradient-bg.gif/1.1/Sat Mar 10 05:53:52 2007/-kb/
/ns-collapse.gif/1.1/Sat Mar 10 09:32:21 2007/-kb/
www.eeworm.com/read/427489/8940264
m bfgs_u2_f_celu_grad.m
% gradient funkcji celu wzgledem u2
% u2 == x
function q = bfgs_u2_f_celu_grad(x,main_x0,main_h0,main_tau)
h = 1e-6;
for i = 1:length(x)
e = zeros(length(x),1);
e(i) = 1;
xeh = x+e*
www.eeworm.com/read/427489/8940298
asv bfgs_u2_f_celu_grad.asv
% gradient funkcji celu wzgledem u2
% u2 == x
function q = bfgs_u2_f_celu_grad(x,main_x0,main_h0,main_tau)
h = 1e-5;
for i = 1:length(x)
e = zeros(length(x),1);
e(i) = 1;
xeh = x+e*
www.eeworm.com/read/417673/10980906
m gdconv.m
% Illustration of gradient descent.
% J.-S. Roger Jang, June 1993
a=1;b=1;c=1;d=-1;e=1;
xx=-3:.2:3;
yy=-3:.2:3;
[x,y]=meshgrid(xx,yy);
cx1 = 1.5; cy1 = -1; % center for the first bowl
z1 = (1+2*(x-cx
www.eeworm.com/read/467198/7020113
m gdconv.m
% Illustration of gradient descent.
% J.-S. Roger Jang, June 1993
a=1;b=1;c=1;d=-1;e=1;
xx=-3:.2:3;
yy=-3:.2:3;
[x,y]=meshgrid(xx,yy);
cx1 = 1.5; cy1 = -1; % center for the first bowl
z1 = (1+2*(x-cx
www.eeworm.com/read/298297/7968128
m nnidbpa.m
% 自适应学习率的bp算法辨识nonlinearFn1.m
% (Gradient descent with adaptive lr backpropagation) nnidbpa.m
% un=2*rand(1,N)-1;
%
%songying, 2005-6-13
% 不会出现nnidbp.m中的仿真异常情况;
% 多数情况下拟合很好：最终eta = 0.0239
www.eeworm.com/read/143498/12870605
m gdconv.m
% Illustration of gradient descent.
% J.-S. Roger Jang, June 1993
a=1;b=1;c=1;d=-1;e=1;
xx=-3:.2:3;
yy=-3:.2:3;
[x,y]=meshgrid(xx,yy);
cx1 = 1.5; cy1 = -1; % center for the first bowl
z1 = (1+2*(x-cx