代码搜索：optimization
找到约 10,000 项符合「optimization」的源代码
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www.eeworm.com/read/241192/13164299
m shootout.m
% Square root covariance filtering "shootout" on an
% ill conditioned problem from P. Dyer & S. McReynolds,
% "Extension of square-root filtering to include process noise"
% Journal of Optimization
www.eeworm.com/read/138798/13212173
m graddesc.m
function [x, options, flog, pointlog] = graddesc(f, x, options, gradf, ...
varargin)
%GRADDESC Gradient descent optimization.
%
% Description
% [X, OPTIONS, FLOG, POINTLOG] = GRADDESC(F, X, OP
www.eeworm.com/read/323757/13321480
c resample_mmx.c
// MMX optimizations from Michael Niedermayer (michaelni@gmx.at) (under GPL)
/* optimization TODO / NOTES
movntq is slightly faster (0.5% with the current test.c benchmark)
(but thats just te
www.eeworm.com/read/321971/13391652
m trainpso.m
%TRAINPSO Particle Swarm Optimization backpropagation.
%
% Syntax
%
% [net,tr,Ac,El] = trainpso(net,Pd,Tl,Ai,Q,TS,VV,TV)
% info = trainpso(code)
%
% Description
%
% TRAINPSO is a
www.eeworm.com/read/318840/13471274
m shootout.m
% Square root covariance filtering "shootout" on an
% ill conditioned problem from P. Dyer & S. McReynolds,
% "Extension of square-root filtering to include process noise"
% Journal of Optimization
www.eeworm.com/read/316143/13529566
m trainpso.m
%TRAINPSO Particle Swarm Optimization backpropagation.
%
% Syntax
%
% [net,tr,Ac,El] = trainpso(net,Pd,Tl,Ai,Q,TS,VV,TV)
% info = trainpso(code)
%
% Description
%
% TRAINPSO is a
www.eeworm.com/read/315324/13545926
m cubic_inter.m
% Program: cubic_inter.m
% Title: Cubic Interpolation Search
% Description: Implements the cubic interpolation search.
% Theory: See Practical Optimization Sec. 4.6
% Input:
% fname: objective
www.eeworm.com/read/314385/13568733
m shootout.m
% Square root covariance filtering "shootout" on an
% ill conditioned problem from P. Dyer & S. McReynolds,
% "Extension of square-root filtering to include process noise"
% Journal of Optimization
www.eeworm.com/read/312163/13617625
m contents.m
% Optimization methods for STPRtoolbox.
%
% gmnp - Solves Generalized Minimal Norm (GMNP) problem.
% gnnls - Solves Generalized Non-negative Least Squares (GNNLS) problem.
% gnpp - S
www.eeworm.com/read/311695/13626989
m trainpso.m
%TRAINPSO Particle Swarm Optimization backpropagation.
%
% Syntax
%
% [net,tr,Ac,El] = trainpso(net,Pd,Tl,Ai,Q,TS,VV,TV)
% info = trainpso(code)
%
% Description
%
% TRAINPSO is a