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本书全面介绍了数据挖掘，涵盖了五个主题：数据、分类、关联分析、聚类和异常检测。除异常检测外，每个主题都有两章：前一章涵盖基本概念、代表性算法和评估技术，而后一章讨论高级概念和算法。这样读者在透彻地理解数据挖掘的基础的同时，还能够了解更多重要的高级主题。 (Introduction to Data Mining Instructor’s Solution )

第二代curvelet变换工具箱，有快速傅里叶变换和wraping变换方法，还可以提取变换系数。有matlab版本和c++版本(The second generation of curvelet transform toolbox, with fast Fourier transform and wraping transform method, also can extract transform coefficient.With the matlab version and c++ version)

rapport de stage industriel

it is overlap add method for signals

finit difference waveguide

Kmeans聚类算法的一个示例 是一个简单的程序但是体现了思想(a simple example of K-means algorthm which contains the core thinking method of clustering)

基于simulink的AGV数字仿真，采用PID控制(AGV digital simulation based on Simulink and PID control)

File that simulate power systems

MATlab工具箱的多元优化求解问题，自己进行了一点更改，希望能够好用(MATlab optimization toolbox to solve diverse problems, themselves a little change in the hope of easy to use)

pitch detection with correlation