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/113576/15453055

m gradwbfixed.m

function [grad] = gradwbfixed(Sigma,indsup,Alpsup,w0,C,Xapp,yapp,Sigmaold,pow); %GRADWBFIXED Computes the gradient of an upper bound on SVM loss wrt SIGMA^POW % GRAD = GRADWBFIXED(SIGMA,INDSUP,ALPS
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www.eeworm.com/read/111593/15509575

java tanktower.java

import java.awt.*; public class tankTower{ public double x, y, z; public int width, length, height, distanceToGround, distanceToCentre; public vector centre, normal, gradient, direction2D, di
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www.eeworm.com/read/111593/15509578

java ssmtower.java

import java.awt.*; public class SSMtower{ public double x, y, z; public int width, length, height, distanceToGround, distanceToCentre; public vector centre, normal, gradient, direction2D, dir
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www.eeworm.com/read/111593/15509589

java tankbody.java

import java.awt.*; public class tankBody{ public double x, y, z; public int width, length, height, distanceToGround, distanceToCentre; public vector centre, normal, gradient, direction2D, dir
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www.eeworm.com/read/111593/15509593

java ssmbody.java

import java.awt.*; public class SSMbody{ public double x, y, z; public int width, length, height, distanceToGround, distanceToCentre; public vector centre, normal, gradient, direction2D, dire
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www.eeworm.com/read/390106/8483592

htm color_setgradient.htm

Drawing with a Gradient Color (Java Developers Almanac Example)
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www.eeworm.com/read/377948/9256344

m nnd12cg.m

function nnd12cg(cmd,arg1) %NND12CG Conjugate gradient backpropagation demonstration. % % This demonstration requires the Neural Network Toolbox. % First Version, 8-31-95. %==================
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www.eeworm.com/read/365849/9844272

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 xltv
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www.eeworm.com/read/365849/9844283

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 xtab
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www.eeworm.com/read/365849/9844344

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 xtab
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