javascript中文教程 <INPUT TYPE="button" NAME="objectName" VALUE="buttonText" [onClick="handlerText"]> NAME specifies the name of the button object as a property of the enclosing form object and can be accessed using the name property. VALUE specifies the Label to display on the button face and can be accessed using the value property.
標(biāo)簽： javascript buttonText objectName onClick
上傳時(shí)間： 2014-01-25
上傳用戶：aix008
我對(duì)mo安裝目錄下VB的MoView例子的frmIdentify窗體修改，其中添加 了1個(gè)Label空件組(10個(gè))，1個(gè)text控件組(10個(gè))，2個(gè)command(Edit 、Save)按鈕,要實(shí)現(xiàn)的功能是對(duì)讀入的圖形文件的相關(guān)記錄的指定字段的 屬性值，并能保存，用了Recordset對(duì)象的Edit函數(shù)、Update函數(shù)，
標(biāo)簽： frmIdentify MoView 目錄 修改
上傳時(shí)間： 2016-04-28
上傳用戶：as275944189
可拖動(dòng)按鈕，包括button,Label,panel,picturebox等。
標(biāo)簽： 按鈕
上傳時(shí)間： 2016-05-29
上傳用戶：gtf1207
* acousticfeatures.m: Matlab script to generate training and testing files from event timeseries. * afm_mlpatterngen.m: Matlab script to extract feature information from acoustic event timeseries. * extractevents.m: Matlab script to extract event timeseries using the complete run timeseries and the ground truth/Label information. * extractfeatures.m: Matlab script to extract feature information from all acoustic and seismic event timeseries for a given run and set of nodes. * sfm_mlpatterngen.m: Matlab script to extract feature information from esmic event timeseries. * ml_train1.m: Matlab script implementation of the Maximum Likelihood Training Module. ?ml_test1.m: Matlab script implementation of the Maximum Likelihood Testing Module. ?knn.m: Matlab script implementation of the k-Nearest Neighbor Classifier Module.
標(biāo)簽： acousticfeatures timeseries generate training
上傳時(shí)間： 2013-12-26
上傳用戶：牛布牛
調(diào)整圖形的明暗對(duì)比 顏色漸層表單 如何使Form的背景圖隨Form大小改變 做出分隔線 如何并排圖形，以填滿Form Form改變大小時(shí)同時(shí)改變其內(nèi)Control之大小 判別圖形中Mouse Click是在其中哪個(gè)子圖上發(fā)生 閃爍的Label 具有ScrollBar的表單
上傳時(shí)間： 2014-01-13
上傳用戶：sssl
MTOOLS version 2.0 Mtools is a public domain collection of programs to allow Unix systems to read, write, and manipulate files on an MSDOS filesystem (typically a diskette). The following MSDOS commands are emulated: Mtool MSDOS name equivalent Description ----- ---- ----------- mattrib ATTRIB change MSDOS file attribute flags mcd CD change MSDOS directory mcopy COPY copy MSDOS files to/from Unix mdel DEL/ERASE delete an MSDOS file mdir DIR display an MSDOS directory mformat FORMAT add MSDOS filesystem to a low-level format mLabel Label make an MSDOS volume Label. mmd MD/MKDIR make an MSDOS subdirectory mrd RD/RMDIR remove an MSDOS subdirectory mread COPY low level read (copy) an MSDOS file to Unix mren REN/RENAME rename an existing MSDOS file mtype TYPE display contents of an MSDOS file mwrite COPY low level write (copy) a Unix file to MSDOS
標(biāo)簽： collection programs version systems
上傳時(shí)間： 2016-11-18
上傳用戶：wlcaption
這是個(gè)簡(jiǎn)單的DELPHI加法器程序，其中用了Label部件，BUTTON部件，EDIT部件，初學(xué)者可以看看。
上傳時(shí)間： 2017-03-12
上傳用戶：liglechongchong
電腦家電控制系統(tǒng) 本系統(tǒng)是利用電腦通過串口和單片機(jī)進(jìn)行通信，從而通過電腦控制家電的開和關(guān)，也可用于其它地方控制其它電器。 此系統(tǒng)制作資料齊全，也很簡(jiǎn)單。 電腦上位機(jī)軟件下載 電路原理圖和PCB板圖下載 源程序下載 1.本系統(tǒng)可以通過PC遠(yuǎn)程或者在家控制家用電器，為適應(yīng)各種場(chǎng)合，只需更改上位機(jī)相應(yīng)的Label的名稱即可！（這點(diǎn)也是這個(gè)軟件的不足之一，會(huì)在以后的時(shí)間里，慢慢完善。） 2.硬件原理圖中，三端穩(wěn)壓管7805，未加任何散熱裝置，經(jīng)實(shí)驗(yàn)，由于電流過大，可能會(huì)導(dǎo)致7805的損壞！解決辦法如下： （1）加裝散熱片 （2）在7805的輸出端接個(gè)大功率三級(jí)管來擴(kuò)流！ 3.因涉及到220V市電，實(shí)驗(yàn)時(shí)，請(qǐng)務(wù)必注意人身安全！！！
標(biāo)簽： 電腦 家電控制系統(tǒng) 串口 單片機(jī)
上傳時(shí)間： 2017-07-25
上傳用戶：moerwang
自己編寫代碼實(shí)現(xiàn)了kmeans算法，輸入變量 data 為 N 行 m 列，每一行為一個(gè)數(shù)據(jù)點(diǎn)，num 表示聚類數(shù)目；輸出變量 Label 為 N 行 1 列， 表示對(duì)應(yīng)的數(shù)據(jù)點(diǎn)屬于哪一類。
上傳時(shí)間： 2016-05-31
上傳用戶：lmeeworm
In this paper we present a classifier called bi-density twin support vector machines (BDTWSVMs) for data classification. In the training stage, BDTWSVMs first compute the relative density degrees for all training points using the intra-class graph whose weights are determined by a local scaling heuristic strategy, then optimize a pair of nonparallel hyperplanes through two smaller sized support vector machine (SVM)-typed problems. In the prediction stage, BDTWSVMs assign to the class Label depending on the kernel density degree-based distances from each test point to the two hyperplanes. BDTWSVMs not only inherit good properties from twin support vector machines (TWSVMs) but also give good description for data points. The experimental results on toy as well as publicly available datasets indicate that BDTWSVMs compare favorably with classical SVMs and TWSVMs in terms of generalization
標(biāo)簽： recognition Bi-density machines support pattern vector twin for
上傳時(shí)間： 2019-06-09
上傳用戶：lyaiqing
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