是个定时期,不是太有用的东西,

遗传算法，是模拟达尔文的遗传选择和自然淘汰的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法.遗传算法是一类可用于复杂系统优化的具有鲁棒性的搜索算法-Genetic algorithm, is a simulation of Darwinian natural selection to genetic selection and biological evolution of the computing model is a natural evolutionary process by simulating the optimal solution search methods. Is a kind of genetic algorithm can be used for optimization of complex systems is robust The search algorithm

The Matlab Toolbox for Pattern Recognition

我的八数码游戏！！ 学人工智能的编写的-my eight digital game! ! The study prepared by the Artificial Intelligence

利用神经网络解决控制论的问题.很好地阐述了这一问题的解决方法.-The use of neural networks to solve the problem of control theory. A very good description of the problem solution.

昨天刚刚看到的A star算法类的实现，不知道对大家有没有用，参考一下吧-Yesterday, I saw a star of the algorithm to achieve category, we do not know of any use it for reference

十折交叉验证方法的matlab code 再模式识别中是一个非常重要的试验方法-a very important technique crossvalidate in pattern recognazition

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 ...

模式识别中的十大经典算法,有详细的实现过程,花了很大工夫,现挥泪上传-Ten classic pattern recognition algorithms in detail the realization of the process and spent a lot of work, it is挥泪From

自组织 Kohonen 映射程序，当一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。 -Kohonen self-organizing map process, when a neural network to outside input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is done automatically. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method.

网络能通过学习带正确答案的实例集自动提取“合理的”求解规则，即具有自学习能力-network can learn the correct answer with examples of automatic drawing of the "reasonable" solution rules, that is self-learning ability