代码搜索：Simulated
找到约 1,823 项符合「Simulated」的源代码
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www.eeworm.com/read/160819/10495816
h gballoonx.h
#ifndef _GBALLOON_H
#define _GBALLOON_H
// class for balloon manipulation using simulated auto pilot
// (based on an idea of Dave Reed) graphics version 3/22/99
//
// Ascend: rise to specified
www.eeworm.com/read/351288/10662097
txt readme.txt
FRF.mat contain:
FRF(:,1) = Frequency range vector (rad/sec).
FRF(:,2) = The simulated Frequency Response Function using as input=1 and output=3
(see: MATLAB Central>File Exc
www.eeworm.com/read/421516/10733087
m m1o.m
% M file for Project 1 on induction motor drive
% with open loop control in Chapter 9
% It sets the machine parameters and also plots the simulated
% results when used in conjunction with s1open.m
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m m1o.m
% M file for Project 1 on induction motor drive
% with open loop control in Chapter 9
% It sets the machine parameters and also plots the simulated
% results when used in conjunction with s1open.m
www.eeworm.com/read/399996/7816722
m stochastic_sa.m
function [patterns, targets] = Stochastic_SA(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the stochastic simulated annealing algorithm
%Inputs:
% train_
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m dbtex1.m
function dbtex1
%DBTEX1 An example of a main program using MUSIC and conventional beamforming on simulated signals from an ULA.
%
% * DBT, A Matlab Toolbox for Radar Signal Processing *
% (c) FO
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m stochastic_sa.m
function [patterns, targets] = Stochastic_SA(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the stochastic simulated annealing algorithm
%Inputs:
% train_
www.eeworm.com/read/245941/12770846
m stochastic_sa.m
function [patterns, targets] = Stochastic_SA(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the stochastic simulated annealing algorithm
%Inputs:
% train_
www.eeworm.com/read/330850/12864856
m stochastic_sa.m
function [patterns, targets] = Stochastic_SA(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the stochastic simulated annealing algorithm
%Inputs:
% train_
www.eeworm.com/read/317622/13500852
m stochastic_sa.m
function [patterns, targets] = Stochastic_SA(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the stochastic simulated annealing algorithm
%Inputs:
% train_