一个牛人的神经网络支持向量机程序,对于搞神经网络的朋友强烈推荐.第二部分...

内附两个源代码，其中一个源代码是识别程序的，另一个是一个矩阵类库的，所以一并附上。 ~..~因为已经保存了训练好的网络权值，所以第一次使用识别程序时，可以直接运行Release目录下的可执行文件，然后对图片目录中的测试图片进行读入、识别。 当然读者也可以自行用训练样本训练网络，不过要特别注意训练样本的选择，否则可能造成识别率很低。训练样本选择的原则是，尽可能的有代表性，在训练时间不至于太长的情况下，训练样本数目尽量多。 -containing 2 source code, which is a source identification procedures, and the other is a matrix class library. So accompanied. ~ ~ .. Has been preserved because of the trained network weights, the first use of the identification procedures, can be run directly Release directory executable file, Then the catalog of tests conducted read into the picture, recognition. Certainly readers can use their own training samples training network, but special attention should be paid to the choice of training samples, Otherwise, it could cause a very low recognition rate. Training sample selection principle is that as far as possible be representative, in the training of the time not too long under the circumstances, the number of training samples as much as possible.

利用VC实现的贝叶斯分类器的源代码，可以用来分类或识别，很值得收藏-The source code of bayes classfication using VC

加法难题 有如下的加法算式： donald + gerald = robert 每个字母代表一个不同的数字(0-9)，你能否求出每个字母分别代表什么数字？-Adder problems with the additive formula is as follows : donald gerald = robert each letter representing a different figures (0-9), Can you calculated each letter on behalf of what?

这是一个识别两句话之间的相似度的程序，输入是两句中文文字，输出是得分（满分100）-This is a recognition of the similarity between two sentences of the procedure, the input of two Chinese characters, the output is a score (out of 100)

图像检测模板匹配的Visual C++代码-Image Detection template matching Visual C code

遗传算法的经典程序，初学者一定要-GA classic procedures, beginners must look good

求最优值的一个算法-seeking an optimal value of the algorithm

基于遗传算法的分词论文 基于遗传算法的分词论文-Segmentation Based on Genetic Algorithms PapersSegmentation Based on Genetic Algorithms PapersSegmentation Based on Genetic Algorithms Papers

贝叶斯（Bayesion）机器学习相互信息。用于求取熵、联合熵等。改进后可用于随机反演-Bayesian (Bayesion) machine learning of mutual information. Used to obtain entropy, joint entropy and so on. Improved can be used for stochastic inversion

模式识别分类程序，贝叶斯，神经网络分类训练程序，很不错啊-the classification procedures, Bayesian neural network classifier training procedures, and it is very responds :