代码搜索:ordered
找到约 1,143 项符合「ordered」的源代码
代码结果 1,143
www.eeworm.com/read/405479/2289204
java group.java
package org.hibernate.test.manytomany.ordered;
import java.io.Serializable;
import java.util.List;
import java.util.ArrayList;
public class Group implements Serializable {
private Long id;
www.eeworm.com/read/402224/2326685
properties jbpm.business.calendar.properties
hour.format=HH:mm
#weekday ::= [ [& ]*]
#daypart ::= -
#start-hour and to-hour must be in the hour.format
#dayparts have to be ordered
weekday.monday= 9:
www.eeworm.com/read/402224/2326914
properties jbpm.business.calendar.properties
hour.format=HH:mm
#weekday ::= [ [& ]*]
#daypart ::= -
#start-hour and to-hour must be in the hour.format
#dayparts have to be ordered
weekday.monday= 9:
www.eeworm.com/read/395296/2440436
pro plugins.pro
TEMPLATE = subdirs
CONFIG += ordered
REQUIRES = !CONFIG(static,shared|static)
contains(QT_CONFIG, qt3support): SUBDIRS += widgets
win32:!contains(QT_EDITION, OpenSource):SUBDIRS += activeqt
# contain
www.eeworm.com/read/108859/15573958
m fftplot.m
function [y,f] = fftplot(x,t)
% FFTPLOT FFT magnitude and phase spectra.
%
% [Z,f] = FFTPLOT(X,TS) FFT magnitude and phase specta (re-ordered).
% X = signal vector/array with sampling int
www.eeworm.com/read/428451/8867354
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/427586/8932237
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/183445/9158785
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/374698/9388956
m bay_lssvmard.m
function [inputs,ordered,costs,sig2n,model] = bay_lssvmARD(model,type,btype,nb);
% Bayesian Automatic Relevance Determination of the inputs of an LS-SVM
%
%
% >> dimensions = bay_lssvmARD({X,Y,type,
www.eeworm.com/read/168218/9932009
cdat
.nr H1 4
.oh "The Abstract Data Type"
.eh "Stacks"
.CS
STACKS
.CE
.NH 2
THE ABSTRACT DATA TYPE
.LP
.sp
A \fIstack\fR is an ordered list
of elements. One end of this list is designated the