代码搜索:Gradients

找到约 319 项符合「Gradients」的源代码

代码结果 319
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pde radialgradient.pde

/** * Simple Radial Gradient * by Ira Greenberg. * * Using the convenient red(), green() * and blue() component functions, * generate an array of radial gradients. */ void setup(){ size
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c dribble.c

/* # proc: dribble_down_up - given an image and a starting x position, follows the gradients # proc: of character stroke edges from the top of the image down and # proc:
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bib paper.bib

@Article{fletcher, author = {R[] Fletcher and C[] M[] Reeves}, title = {Function minimization by conjugate gradients}, journal = {Computer Journal}, year = 1964, volume = 7, pages
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m grinprodgausquad.m

function int=grinprodgausquad(g,sigma); %grinprodgausquad Computes the integral of the product of the gradients in 2D FEM for quadratic isoparametric triangular elements % Function int=grinprodgausqu
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m initgradients.m

function obj=initgradients(obj) % Initializes the gradients of the data objects f and h. % % Syntax: (* = optional) % % model = initgradients(model); % % In arguments: % % 1. model % Model o
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m initgradients.m

function obj=initgradients(obj) % Initializes the gradients of the data objects f and h. % % Syntax: (* = optional) % % model = initgradients(model); % % In arguments: % % 1. model % Model o
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m initgradients.m

function obj=initgradients(obj) % Initializes the gradients of the data objects f and h. % % Syntax: (* = optional) % % model = initgradients(model); % % In arguments: % % 1. model % Model o
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m calcbasis.m

function [fparm,gparm,gradf,gradg] = calcbasis(parmvec,basisfunc) % function [fparm,gparm,gradf,gradg] = calcbasis(parmvec,'basisfunc') % % Evaluates basis functions and gradients at desired parame
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m initgradients.m

function obj=initgradients(obj) % Initializes the gradients of the data objects f and h. % % Syntax: (* = optional) % % model = initgradients(model); % % In arguments: % % 1. model % Model o
www.eeworm.com/read/325790/13185203

m initgradients.m

function obj=initgradients(obj) % Initializes the gradients of the data objects f and h. % % Syntax: (* = optional) % % model = initgradients(model); % % In arguments: % % 1. model % Model o