开发环境：Visual C++ .net2003 功能：利用禁忌搜索思想求解TSP问题。...

这是 qpsk 调制方案的模拟。在 simulink 中模拟了 QPSK 和已绘制了误码率和信噪比曲线。使用的通道是 AWGN 信道下。

POKER 计算值   斗地主  扎金花都离不开它  This article for the budding poker AI programmer provides a foundation for a simple implementation of No-Limit Texas Holdem Poker AI, covering the basics of hand strength evaluation and betting. By following the recipe set out here, you will quickly become able to implement a reasonably strong poker AI, and have a solid foundation on which to build. I assume you are familiar with the basic terminology of poker.

误差分析的方法有多种，这是一种先验估计误差的方法，较以往的“向前误差分析”在矩阵运算的舍入误差估计上有较好的结果，以而使矩阵的误差分析获得了突破性的进展，使不少用向前误差分析难于判定可靠性的数值方法获得新的进展。特别值得一提的是，在工程技术界，经常使用几种不同的计算方法，甚至使用实验方法进行比较，从而确定计算结果的可靠性，这也是一种有效而实用的方法。-error analysis by a number of means, which is a priori estimation error method, compared to the previous "Forward Error Analysis" in the matrix calculation error into the homes a better estimate on the results of a matrix so the error analysis of a breakthrough in the progress, many with forward error analysis can be difficult to determine on the numerical method to achieve new progress. Particularly worth mentioning is that in the engineering technology sector, often use several different methods of calculation, or even the use of experimental methods, in order to determine the reliability of results, which is also an effective and practical method.

Numerical Anaysis 8th Edition Burden and Faires

C常用数值算法－－特征函数-C commonly used numerical algorithm-- eigenfunction

运筹学很有用的程序，线性规划课本里的习题答案，求解线性规划问题-Useful operational research procedures, linear programming exercises in the textbook answer for solving linear programming problems

HMM中经典的前向后向算法，带有比例因子-classical HMM back to the first algorithm, with a scale factor

一个加载Ezwin的费式序列的动态演示-a load Ezwin the fee-demonstration of the dynamic sequence! !

使用C语言对图形进行读取和处理，在过程中将bmp（位图）文件进行读取和存储的小小程序

平均因子分解法，适用于正定矩阵First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square matrix X, the Cholesky decomposition of X is the factorization X=U U, where U is the square root matrix of X, and satisfies: (1) U U = X (2) U is upper triangular (that is, it has all zeros below the diagonal). It seems that the assumption of positive definiteness is necessary. Actually, it is "positive definite" which guarantees the existence of such kind of decomposition. -Average factor decomposition method applied to positive definite matrix First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square matrix X, the Cholesky decomposition of X is the factorization X = UU, where U is the square root matrix of X, and satisfies: (1) UU = X (2) U is upper triangular (that is, it has all zeros below the diagonal). It seems that the assumption of positive definiteness is necessary. Actually, it is positive