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/186875/8898522
h implicitfunction.h
#ifndef IMPLICITFUNCTION
#define IMPLICITFUNCTION
#include
class ImplicitFunction{
public:
virtual float value(float x, float y, float z)=0;
virtual void gradient(float g[3], fl
www.eeworm.com/read/185152/9054801
m apprgrdn.m
function g = apprgrdn(x,f,fun,deltax,obj)
% Usage:
% g = apprgrdn(x,f,fun,deltax,obj)
% Function apprgrdn.m performs the finite difference approximation
% of the gradient at a point .
%
www.eeworm.com/read/282683/9074167
m hill_obj.m
function [f,df]=hill_obj(x,dims,ii,dd,pars);
%
% computes the objective function and gradient of the non-convex formulation of MVU.
%
% copyright by Kilian Q. Weinberger, 2006
%
%
%
% This file is
www.eeworm.com/read/184067/9123701
m definev.m
function [v,dv]= definev(g,x,l,u);
%DEFINEV Scaling vector and derivative
%
% [v,dv]= DEFINEV(g,x,l,u) returns v, distances to the
% bounds corresponding to the sign of the gradient g, where
%
www.eeworm.com/read/177674/9442538
m olgd.m
function [net, options, errlog, pointlog] = olgd(net, options, x, t)
%OLGD On-line gradient descent optimization.
%
% Description
% [NET, OPTIONS, ERRLOG, POINTLOG] = OLGD(NET, OPTIONS, X, T) uses on
www.eeworm.com/read/177674/9442574
m gpgrad.m
function g = gpgrad(net, x, t)
%GPGRAD Evaluate error gradient for Gaussian Process.
%
% Description
% G = GPGRAD(NET, X, T) takes a Gaussian Process data structure NET
% together with a matrix X of
www.eeworm.com/read/176823/9483220
m olgd.m
function [net, options, errlog, pointlog] = olgd(net, options, x, t)
%OLGD On-line gradient descent optimization.
%
% Description
% [NET, OPTIONS, ERRLOG, POINTLOG] = OLGD(NET, OPTIONS, X, T) uses on
www.eeworm.com/read/176823/9483256
m gpgrad.m
function g = gpgrad(net, x, t)
%GPGRAD Evaluate error gradient for Gaussian Process.
%
% Description
% G = GPGRAD(NET, X, T) takes a Gaussian Process data structure NET
% together with a matrix X of
www.eeworm.com/read/166306/10024497
m definev.m
function [v,dv]= definev(g,x,l,u);
%DEFINEV Scaling vector and derivative
%
% [v,dv]= DEFINEV(g,x,l,u) returns v, distances to the
% bounds corresponding to the sign of the gradient g, where
%
www.eeworm.com/read/358694/10181644
m definev.m
function [v,dv]= definev(g,x,l,u);
%DEFINEV Scaling vector and derivative
%
% [v,dv]= DEFINEV(g,x,l,u) returns v, distances to the
% bounds corresponding to the sign of the gradient g, where
%