代码搜索：BATCH

找到约 6,125 项符合「BATCH」的源代码

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热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/177129/9468816

m optimal_brain_surgeon.m

function [D, Wh, Wo] = Optimal_Brain_Surgeon(train_features, train_targets, params, region) % Classify using a backpropagation network with a batch learning algorithm and remove excess units % usi
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www.eeworm.com/read/176823/9483149

m kmeans.m

function [centres, options, post, errlog] = kmeans(centres, data, options) %KMEANS Trains a k means cluster model. % % Description % CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means %
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www.eeworm.com/read/372113/9521346

m backpropagation_recurrent.m

function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation recurrent network with a batch learning algorithm
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www.eeworm.com/read/362008/10024009

m backpropagation_recurrent.m

function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation recurrent network with a batch learning algorithm
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www.eeworm.com/read/358640/10183151

bat cmex.bat

@echo off rem rem CMEX.BAT: Obsoleted batch file for invoking the MEX-file creation script rem rem $Revision: 1.3 $ $Date: 2000/01/04 18:32:25 $
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www.eeworm.com/read/357874/10199188

m backpropagation_recurrent.m

function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation recurrent network with a batch learning algorithm
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www.eeworm.com/read/278099/10571509

c ccomcall.c

/* +++Date last modified: 05-Jul-1997 */ /* ** Call undocumented Int 2Eh to invoke COMMAND.COM ** ** demo by Bob Stout ** ** NOTES: Dangerous code - will abort batch files in progress and
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www.eeworm.com/read/349842/10796734

m optimal_brain_surgeon.m

function [D, Wh, Wo] = Optimal_Brain_Surgeon(train_features, train_targets, params, region) % Classify using a backpropagation network with a batch learning algorithm and remove excess units % usi
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www.eeworm.com/read/469416/6976421

m kmeansnetlab.m

function [centres, options, post, errlog] = kmeans(centres, data, options) %KMEANS Trains a k means cluster model. % % Description % CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-mean
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www.eeworm.com/read/449504/7502312

m kmeans.m

function [center, U, distortion] = kmeans(dataSet, clusterNum, plotOpt) %KMEANS K-means clustering using Forgy's batch-mode method % Usage: [center, U, distortion] = KMEANS(dataSet, clusterNum) %
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