代码搜索：optimization
找到约 10,000 项符合「optimization」的源代码
代码结果 10,000
www.eeworm.com/read/472938/6306883
m pso2.m
%% Particle Swarm Optimization Simulation
% Simulates the movements of a swarm to minimize the objective function
%
% $$ \left( x-15 \right) ^{2}+ \left( y-20 \right) ^{2} = 0$$
%
% The swarm m
www.eeworm.com/read/456267/6332178
m pso.m
%% Particle Swarm Optimization Simulation
% Simulates the movements of a swarm to minimize the objective function
%
% $$ \left( x-15 \right) ^{2}+ \left( y-20 \right) ^{2} = 0$$
%
% The swarm m
www.eeworm.com/read/486842/6530685
c svm_smo.c
/* Copyright (C) 1999 Greg Schohn - gcs@jprc.com */
/* ********************* svm_smo.c **********************
* John Platt's Sequential Minimal Optimization algorithm
* (http://www.research.micros
www.eeworm.com/read/485544/6552698
m contents.m
% Netlab Toolbox
% Version 3.2.1 31-Oct-2001
%
% conffig - Display a confusion matrix.
% confmat - Compute a confusion matrix.
% conjgrad - Conjugate gradients optimization.
% consist - Ch
www.eeworm.com/read/485544/6552722
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, OPTIONS
www.eeworm.com/read/481753/6637920
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/478401/6716215
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/410537/11278866
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/347943/11626794
m feascpx.m
% FEASCPX Generates a random sparse optimization problem with
% linear, quadratic and semi-definite constraints. Output
% can be used by SEDUMI. Includes complex-valued data.
%
% The followi
www.eeworm.com/read/347557/11657989
m func_ant_colony_image_edge_detection.m
function func_ant_colony_image_edge_detection
%
%
% This is a demo program of image edge detection using ant colony, based on
% the paper, "An Ant Colony Optimization Algorithm For Image Edge
% D