hough变换的代码，这个变换可以原来检测直线或圆等图形。

用模拟退火算法解决TSP问题，在C运行环境中-TSP with ant colony algorithm to solve the problem in the C runtime environment

这是反向传播算法的C++程序，对于研究BPNN的人来说，具有很好的参考价值-This is the back-propagation algorithm C program for studying the BPNN people, have a good reference value

【机器学习】文本分类源代码 【机器学习】文本分类源代码 -] [Machine learning text classification source code] [machine learning text classification source code

遗传算法的简单程序，可用于离散变量优化，多目标优化等许多领域-the simple procedure can be used for optimization of discrete variables, such as multi-objective optimization in many areas

我们解决八数码问题,广度优先搜索可能会导致内存不够用,采用启发式搜索,启发函数为f(x)=g(x)+h(x) g(x)为该结点不同于目标结点的个数,h(x)为该结点的深度,选择那f(x)结点最小的那个结点进行扩展, 引入了一个"扩展数组[4]"(因为扩展的结点最多只有4个),该数组保存着某个结点的0点向各个方向的扩展的结点对象,然后对该扩展数组进行分析,利用启发函数在进行递归扩展... -us solve eight digital, BFS may lead to insufficient memory, using heuristic search, heuristic function f (x) = g (x) h (x) g (x) for the target node is different from the number of nodes, h (x) for the nodes of depth, the choice between f (x) nodes that the smallest node expansion. the introduction of an "expanded array [4]" (because the expansion of the nodes at most four), The array maintains a node of 0:00 a.m. to expand in all directions in the target node, and then expanded array analysis, use heuristic function during recursive expansion ...

免疫算法求解函数优化问题运行时请选择所要的函数,并且点Button1执行-immune function algorithm optimization runtime please select the function and implementation point Button1

经典的数据关联挖掘算法prefixspan-Classical data association mining algorithm PrefixSpan

小波神经网络的MATLAB程序，没有用库函数-Wavelet Neural Network MATLAB procedures, did not use library functions

介绍了神经 网络中的ADALINE算法的C语言实现.-Introduction of the ADALINE neural network algorithm in C language.

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.-particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.