代码搜索：Gradient

找到约 2,951 项符合「Gradient」的源代码

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m colorgrad.m

function [VG, A, PPG]= colorgrad(f, T) %COLORGRAD Computes the vector gradient of an RGB image. % [VG, VA, PPG] = COLORGRAD(F, T) computes the vector gradient, VG, % and corresponding angle arr
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www.eeworm.com/read/162188/10327691

dec optmum.dec

/* ** optmum.dec - declarations for globals used in OPTMUM. ** (C) Copyright 1988-1999 by Aptech Systems, Inc. ** All Rights Reserved. ** ** This Software Product is PROPRIETARY SOURCE CODE OF AP
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www.eeworm.com/read/162188/10327815

src maxlik.src

/* ** maxlik.src MAXLIK - Maximum Likelihood Estimation ** ** ** (C) Copyright 1988-1997 Aptech Systems, Inc. ** All Rights Reserved. ** ** This Software Product is PROPRIETARY SOURCE CODE
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www.eeworm.com/read/162188/10327959

src optmum.src

/* ** optmum.src - General Nonlinear Optimization ** (C) Copyright 1988-1998 by Aptech Systems, Inc. ** All Rights Reserved. ** ** This Software Product is PROPRIETARY SOURCE CODE OF APTECH ** S
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www.eeworm.com/read/162075/10341941

m netgrad.m

function g = netgrad(w, net, x, t) %NETGRAD Evaluate network error gradient for generic optimizers % % Description % % G = NETGRAD(W, NET, X, T) takes a weight vector W and a network data % structure
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m scg.m

function [x, options, flog, pointlog, scalelog] = scg(f, x, options, gradf, varargin) %SCG Scaled conjugate gradient optimization. % % Description % [X, OPTIONS] = SCG(F, X, OPTIONS, GRADF) uses a sca
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www.eeworm.com/read/425546/10348994

m netgrad.m

function g = netgrad(w, net, x, t) %NETGRAD Evaluate network error gradient for generic optimizers % % Description % % G = NETGRAD(W, NET, X, T) takes a weight vector W and a network data % stru
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www.eeworm.com/read/425546/10349155

m glmgrad.m

function [g, gdata, gprior] = glmgrad(net, x, t) %GLMGRAD Evaluate gradient of error function for generalized linear model. % % Description % G = GLMGRAD(NET, X, T) takes a generalized linear mode
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www.eeworm.com/read/424063/10501621

m contents.m

% Optimization Toolbox. % Version 1.0d 1-Mar-94 % % Nonlinear minimization of functions. % attgoal - Multi-objective goal attainment. % constr - Constrained minimization. % fmin
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m cedifdemo.m

% CEDIFDEMO Coherence enhancing diffusion demonstration % % Type CEDIFDEMO % clc disp('_____________________________Coherence enhancing diffusion demonstration________________________') d
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