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/366422/9816027

m shili24.m

function shili24 h0=figure('toolbar','none',... 'position',[200 150 450 350],... 'name','实例24'); subplot(2,2,1) z=peaks; ribbon(z) title('Figure1') subplot(2,2,2) [x,y,z]=peaks(15);
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www.eeworm.com/read/170146/9817199

java colorgradient.java

/////////////////////////////////////////////////////////// // DeJaved by mDeJava v1.0. Copyright 1999 MoleSoftware. // // To download last version of this software: // // htt
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www.eeworm.com/read/365849/9844100

m gradx.m

function v=gradx(obj,x,t,w,u) % Evaluates the gradient object at time t, with respect to x. % % Syntax: (* = optional) % % v = gradx(obj, x, t, w, u); % % In arguments: % % 1. obj % The xsym
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www.eeworm.com/read/365849/9844199

m gradw.m

function v=gradw(obj,x,t,w,u) % Evaluates the gradient object at time t, with respect to w. % % Syntax: (* = optional) % % v = gradw(obj, x, t, w, u); % % In arguments: % % 1. obj % The xsym
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www.eeworm.com/read/365849/9844354

m gradx.m

function v=gradx(obj,x,t,w,u) % Evaluates the gradient object at time t, with respect to x. % % Syntax: (* = optional) % % v = gradx(obj, x, t, w, u); % % In arguments: % % 1. obj % The xlin
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www.eeworm.com/read/365849/9844419

m gradw.m

function v=gradw(obj,x,t,w,u) % Evaluates the gradient object at time t, with respect to w. % % Syntax: (* = optional) % % v = gradw(obj, x, t, w, u); % % In arguments: % % 1. obj % The xlin
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www.eeworm.com/read/365849/9844430

m gradx.m

function v=gradx(obj,varargin) % Evaluates the gradient object at time t, with respect to x. % % Syntax: (* = optional) % % v = gradx(obj, x, t, w, u); % % In arguments: % % 1. obj % The xha
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www.eeworm.com/read/365849/9844498

m gradw.m

function v=gradw(obj,varargin) % Evaluates the gradient object at time t, with respect to w. % % Syntax: (* = optional) % % v = gradw(obj, x, t, w, u); % % In arguments: % % 1. obj % The xha
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www.eeworm.com/read/364985/9884475

m exm07512_1.m

%exm07512_1.m shg;clf; [X,Y] = meshgrid([-2:.2:2]); Z = 4*X.*exp(-X.^2-Y.^2); G=gradient(Z); subplot(1,2,1),surf(X,Y,Z,G) subplot(1,2,2),h=surf(X,Y,Z,G); rotate(h,[-2,-2,0],30,[2,2,0]) colorma
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www.eeworm.com/read/362500/9996127

m cgrdsrch.m

function x=cgrdsrch(beta,kin,t,u) %CGRDSRCH Conjugate gradient optimization for NNPLS % Routine to carry out optimization using a conjugate gradient approach % check is relative change in objecti
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