ls

find_end for bidirectional iterators. Requires partial specialization.

wifi控制软件，连接IP地址和端口就可以控制自己的WIFI控制器，操作简单。(wifi control software, IP address and port can control their WIFI controller, simple operation.)

labview之应用datasocket编程的实例，非常详细的。-LabVIEW Application DataSocket Programming examples, very detailed.

knight online mmorpg - speedhack source for an earlier version of the game.

这是一个2D程序,用DIRECTX9.0写的,请大家一定要注意.(This is a 2D program, using DIRECTX9.0 write, please be aware that.)

管道摩擦系数的计算公式手算无法得到结果，需要借助计算机计算。结合Excel-DNA工具制作成为Excel插件，可以方便使用。(The formula for calculating the coefficient of friction of the pipe cannot be obtained by hand calculation and needs to be calculated by computer. It is easy to use with Excel-DNA tool and Excel plug-in.)

最新的borland社区聊天的客户端程序- The newest borland community chats customer end procedure

This function generates an Additive White Gaussian Noise (AWGN) sample at every call. Its beauty lies in its simplicity! The generated sample set will have zero mean and a standard deviation of 1. Therefore, one can simply scale the output samples by a different standard deviation to generate different noise profiles. To do this scaling, simply multiply the sample with the standard deviation of your choice. This is a very versatile function that can be used in communication system simulations and random number generation in various applications. I have used it in the past while working with channel encoder and decoder simulators.

VB采用最小二乘法演示如何在VB中实现线性拟合和二次拟合，编译时候需要TeeChart5.ocx，已将此文件打包，你无需再下载。新建 Microsoft Excel 工作表.xls里是测试数据，程序会自动读龋这里要说的是： 　　1.1 线性拟合：给定一组数据（xi，yi），i=1，2，…，m，做拟合直线。 　　1.2 二次拟合：给定数据系列（xi，yi），i=1，2，…，m，用二次多项式函数拟合这组数据。作出拟合函数与数据序列的均方误差最校 (VB using the method of least squares linear fit and demonstrates how to implement a quadratic fit in VB compiler when needed TeeChart5.ocx, has packed this file, you do not need to download. Newly built in Microsoft Excel worksheet xls test data, the program will automatically read caries say here is: 1.1 linear fit: Given a set of data (xi, yi), i = 1,2, ..., m, do fitting a straight line. 1.2 quadratic fit: given data series (xi, yi), i = 1,2, ..., m, with a quadratic polynomial function fitting this set of data. Fitting function to the data sequence with the best mean square error correction)

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