代码搜索：BATCH
找到约 6,125 项符合「BATCH」的源代码
代码结果 6,125
www.eeworm.com/read/408881/11366286
java batchupdates.java
/**
* A simple sample to demonstrate Batch Updates.
* Please use jdk1.2 or later version
*/
import java.sql.*;
public class BatchUpdates
{
public static void main(String[] args)
{
Connec
www.eeworm.com/read/405069/11472297
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
www.eeworm.com/read/403390/11517962
bat build.bat
@echo off
rem
rem This batch file builds and preverifies the code for the demos.
rem it then packages them in a JAR file appropriately.
rem
if "%OS%" == "Windows_NT" setlocal
set DEMO=NetworkDem
www.eeworm.com/read/403390/11517966
bat run.bat
@echo off
rem This file runs the corresponded demo.
if "%OS%" == "Windows_NT" setlocal
set DEMO=NetworkDemo
if not exist .\%DEMO%.jad (
echo *** Run this batch file from its location direct
www.eeworm.com/read/156528/11794920
m sep.m
function sep()
% SEP goes once through the scrambled mixed speech signals, x
% (which is of length P), in batch blocks of size B, adjusting weights,
% w, at the end of each block.
%
% I suggest
www.eeworm.com/read/253950/12173432
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
%
www.eeworm.com/read/339665/12211363
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
%
www.eeworm.com/read/150905/12249982
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
%
www.eeworm.com/read/131588/14136223
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
www.eeworm.com/read/129915/14217655
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