镶嵌大图标到任务栏源码

取QQ排名源码,例程结合易语言模块彗星HTTP应用模块.ec，调用API函数实现取QQ排名。(Take QQ ranking source , combined with easy language module routine comet HTTP application module .ec, call the API functions take QQ rankings.)

画分形图案简化版源码，例程程序结合易语言位图操作支持库，调用API函数实现简化的分形图。

易语言与PHP做IP交互源码，例程结合易语言互联网支持库读取PHP网页数据将本机IP传送上去，从而实现源码例程的目标。(Easy language and PHP source code to do IP interaction , combined with routines easy language support library to read Internet pages PHP native IP data transfer up to achieve the objectives source routine.)

EXDUI属性框源码,程序结合易语言ExDui.ec模块模拟实现易语言树形框功能效果。拥有：文本编辑，整数编辑，逻辑，列表，颜色选择，字体(字号,风格)选择，按钮7种项目类型！属性框的颜色可以自定义！有自绘接口可以进行扩展绘制.(EXDUI Properties box source code , the program combined with easy language ExDui.ec module simulates the tree box features easy language to achieve results. )

THESE ARE METLAB BOOKS IMPORTANT TO LEARN MATLAB

关于信号与系统的答案，可以帮助同学们更好的学习信号与系统(Answer random signal, can help students better learning with the signal)

说明：  远程代答，需要的朋友们自己下载，谢谢你们的支持我会更加努力的！(Remote Pickup, you need to download their own friends)

查外网IP源码,程序结合易语言第三方支持库WEB浏览器2.0版和易语言模块精易模块 V2.52.ec，实现外网IP的查询。

针对神经网络的瓦斯预测模型存在的泛化性能差且存在易陷入局部最优的缺点，提出了 基于最小二乘支持向量机(LS-SVM)时间序列瓦斯预测方法．由于标准最小二乘支持向量机 (L孓SVM)要求样本误差分布服从高斯分布，且标准LS-SVM丧失鲁棒性与稀疏性等特点，提出 了基于加权LS-SVM的瓦斯时间序列预测的方法，从而提高了标准L孓SVM模型的鲁棒性．其 中时间序列的嵌入维数与延迟时间采用了微熵率最小原则进行选取，在此基础上给出了基于加 权L孓SVM实现多步时间序列预测的算法实现步骤．最后利用MATLAB 7．1对其进行仿真研 究，通过鹤壁十矿1个突出工作面的瓦斯涌出数据实例对模型进行了验证．结果表明，加权 SVM模型比标准的L§SVM明显提高了鲁棒性，可较好地实现时间序列数据的多步预测．(The neural network gas prediction model is poor in generalization performance and easy in fafling into the local optimal value．In order to overcome these shortcomings，we pro— pose the time series gas prediction method of least squares support vector machine(L§SVM)． However，in the LS-SVM case，the sparseness and robustness may lose，and the estimation of the support values iS optimal only in the case of a Gaussian distribution of the error variables． So，this paper proposes the weighted L孓SVM tO overcome these tWO drawbacks．Meanwhile， the optimal embedding dimension and delay time of time series are obtained by the smallest dif— ferential entropy method．On this basis，multi-step time series prediction algorithm steps are given based on the weighted LS-SVM．Finally，the data of gas outburst in working face of Hebi lOth mine iS adopted to validate this model．The results show that the predict effect of shortterm the face gas emission is better using the weighted LS-SVM model than using)

易语言正则表达源码，需要的朋友可以下载来看看，不错的，自己修改。(The easy language regular expression source code, need friends can download to see good, make changes to.)