一个改进的聚类算法FCMA,可以实现数据的自适应有效聚类,对2维数据测试效果较好- An improvement gathers kind of algorithm FCMA, may auto-adapted realize the data effectively to gather the kind, is better to 2 dimensions according to the test effect

模式识别实例工程的源代码-example source code

机器学习讲义机器学习很好的材料内容很全面-Machine Learning Machine Learning Materials Materials is very good all-round

特征提取技术。这种技术以传统的建模方式为前提，对于产生的模型的几何、拓扑等信息加以分析以提取其特征信息，这种技术一般多采用人工智能及模式识别等方面的知识。-feature extraction technology.

这是一个神经网络开发包。目录ann下是专门针对神经网络的代码，外部目录是一些公用的代码，与神经网络无关，但是神经网络的代码用到了它们。 ann目录下有一个目录demo，里面存放了一些示例程序，请参照它们进行编程。-This a neural network development kit. Ann directory under specific neural network code, external directory is some common code, has nothing to do with the neural network, but neural networks use of their code. Ann directory is a directory demo, stored inside a sample program, please refer to their program.

英国svm编写的环境用vc++开发，有完整的源代码，一定会有帮助！

用遗传算法实现任务分配优化的源程序。-genetic algorithm optimization task allocation of the source.

计算欧几里德距离C语言源代码,次源码经测试可有效运行,源码简单易懂-Calculation of Euclidean distance C-language source code, sub-source has been tested and can be effectively run, easy-to-read source

4。《演化程序――遗传算法和数据编码的结合》，[英]米凯利维兹着 科学出版社 2000年第一版 本书分三个部分共16章分别介绍了:1.遗传算法的概念、数学原理及方法步骤 2.遗传算法和数据编码联系起来所构成的演化程序 3.演化程序面向一些实际问题的应用。 本书语言生动，结构合理，较少使用专业性术语和深涩词汇，适合面临优化问题的研究生、程序员、设计师、工程师及科研工作人员参考。-4. "Evolutionary process-- genetic coding algorithm and data integration," [E] Mikhail Liweici a 520-531 2000 version of the first book in three parts a total of 16 chapters were introduced : 1. Genetic Algorithm concept mathematical principles and methods of Step 2. genetic algorithms and data coding linked posed by the evolution of procedures 3. Evolution-oriented procedures some of the practical problems of application. The book vivid language, reasonable structure, and less use of professional terminology and vocabulary deep acerbic suitable for optimization problems facing graduate students, programmers, designers, engineers and research personnel.

遗传算法的源程序例子，对于初学者有很大帮助，建议多-Genetic algorithm source code examples are very helpful for beginners, the proposed multi-