Robot vacuum cleaners cover the whole source simulation algorithm, in the hope t...

代码是数据挖掘技术中使用的，用Java编写。实际上就是数据挖掘技术中决策树的C45算法。

用单纯性法求解线性规划问题，并通过控制台输入系数矩阵。-Using simple method for solving linear programming problems, and through the console input coefficient matrix.

支持向量机的SMO算法-SVM SMO Algorithm

用matlab编写的遗传算法路径规划用matlab编写的遗传算法路径规划源码源码

C++与数据结构简明教程例题源代码1-4章

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列选主元的Gauss消去法-out how the PCA Gaussian Elimination

魔幻方块！输入魔方的阶数n（n为奇数）后，使得魔方的行、列和对角线的值都相等-magic squares! Cube importation of order n (n is odd), the Cube makes rows and columns and diagonal values are equal

爬墙机器人算法的的Python实现，带有GTK图形界面。算法描述如下：当没有墙时，机器人默认向东方移动，触墙后，根据设计的状态机进行方向的转移。该算法可以通过一般的地图测试。

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