代码搜索：Gradient

找到约 2,951 项符合「Gradient」的源代码

代码结果 2,951
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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
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www.eeworm.com/read/413912/11137242

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
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www.eeworm.com/read/413912/11137282

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
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www.eeworm.com/read/334860/12568121

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 %
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www.eeworm.com/read/113576/15453059

m gradwfixed.m

function [grad] = gradwfixed(Sigma,indsup,Alpsup,C,Xapp,yapp,Sigmaold,pow); %GRADWFIXED Computes the gradient of an upper bound on SVM loss wrt SIGMA^POW % GRAD = GRADWFIXED(SIGMA,INDSUP,ALPSUP,C,X
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www.eeworm.com/read/289487/8548505

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/428269/8880185

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/200336/10247150

m costfmin.m

function [f,df,ddf] = costfmin(x, baseMVA, bus, gen, gencost, branch, areas, Ybus, Yf, Yt, mpopt, parms, ccost) %COSTFMIN Evaluates objective function, gradient and Hessian for OPF. % [f, df, ddf]
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www.eeworm.com/read/349479/10824992

m costfmin.m

function [f,df,ddf] = costfmin(x, baseMVA, bus, gen, gencost, branch, areas, Ybus, Yf, Yt, mpopt, parms, ccost) %COSTFMIN Evaluates objective function, gradient and Hessian for OPF. % [f, df, ddf]
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www.eeworm.com/read/466692/7031437

htm experiment12.htm

filter div{ filter: progid:DXImageTransform.Microsoft.Gradient(Gr
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