高性能交流伺服系统及其复合控制策略研究，浙江大学博士论文。 关键词:交流伺服系统，矢量控制，直接转矩控制，复合控制，PID控制，GA，IGA，模糊控制，切换...

1、编制程序显示印章图像（24位真彩色位图）； 2、读出位图中每一像素点的（R，G，B）样本值； 3、以RGB其中某两个（或三个）为坐标，取一定数量的图像点为分析样本，分析其坐标系中的分布； 4、采用本章学习的方法找到分类判别函数，对这些样本进行分类；（要求首先将印章与底纹区分，如有可能将印章、底纹、签字区分） 5、将分类后的结果标记到原始图像上，检查其效果。 -1, the preparation procedures showed that the seal image (24-bit true color bitmap) 2, read out each bitmap pixel (R, G, B) sample value 3 to RGB which a two (or three ) for the coordinates, take a certain number of image points for the analysis of samples, analysis of its coordinate system of distribution 4, the method used in this chapter to learn to find discriminant function classification of these samples for classification (required first to distinguish between the seal and Shading, if possible, will seal, Shading, signatures to distinguish between) 5, will be the result of classification markings to the original image to check its effectiveness.

这是马少平 朱小燕编著的人工智能配套课件，由清华大学出版社出版-This is Ma Shao-ping ZHU Xiao-yan matching artificial intelligence authoring courseware, from Tsinghua University Publishing House

BP神经网络C＋＋实现-BP neural network implemented by C++

这是一本粗糙集的数据挖掘经典书籍，书中不但介绍了粗糙集的相关知识，并给出了相关应用，同时介绍并比较了其他挖掘方法。-This is a rough set data mining classic books, the book not only introduced a rough set of relevant knowledge, and gives the related application, at the same time and compare the introduction of other mining methods.

基本bp神经网络算法和改进型bp神经网络算法都是我改写完成的算法，是网上到处传播的一个c++ bp神经网络算法改写的，由于网上的那个算法编译会出现若干百个错误，在其基础上重新编写和改进，写出了这两个算法-bp basic neural network algorithms and improved neural network algorithm bp I are complete rewrite the algorithm, the Internet is spreading everywhere, a c bp neural network algorithm rewrite the Internet that the algorithm will build several hundred mistakes, on the basis of its rewrite and improve, and wrote a This algorithm 2

最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999. -The newest work tools of svm,it will be very convenient to have it.

数据挖掘算法BIRCH源码 c语言版本。- Data mining algorithm BIRCH source code c language edition.

svm_nu 分类源码 用于svm的分类编程同svm_c 相近-svm classification svm_nu source for the classification of programming with similar svm_c

使用神经网络的K算法来对数据进行分类，有具体的实验要求和图-K using the neural network algorithm to classify the data, there is a specific test requirements and plans

Simulated annealing (SA) for the Symmetric Euclidean TSP