On the Particle Swarm Optimization Algorithm. Using java language.

ISODATA 算法的 C++ 语言的实现源码-ISODATA algorithm C++ Realize language source

用vc实现Apriori算法的全部功能．请大家尽情心使用！-the algorithm can be used vc Apriori algorithm to achieve the full. Please rest assured use! -Apriori algorithm by vc realize the full functionality. Please use your heart!-the algorithm can be used vc Apriori algorithm to achieve the full. Please rest assured use!

神经网络训练算法,很快 很简单 很适用 能快速用到实验环境中去-Neural network training algorithm, is applicable to very quickly is very simple to quickly use the experimental environment

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.

基于倒谱特征的带噪语音端点检测.rar格式为ｖｉｐ-based Cepstral Noisy voice endpoint detection. Rar format vip

利用OPenCV写的一个hough变换检测直线的程序-OPenCV written using a hough transform line detection procedure

bp反向传播算法，用c语言编写，用于航空运输预测。

平时学习时搜集的算法书,聚类,神经网络,蚁群算,遗传算法-some e-books about the algorithm

Robocup机器人小程序,实现了机器人的射门,但机器人之间的配合没有实现-Robocup robot small programs to achieve the goal of a robot, but the robot between the not achieved

是国外相关研究人员提供的发现频繁模式（包括频繁集、频繁子图等）的最新版本算法。-Foreign researchers with the relevant frequent pattern discovery (including frequent itemsets, frequent subgraph, etc.) the latest version of algorithm.