ARecipeforGAMIT

m.file Finger print for image processing applications

Sparse Subspace clustering, an algorithm which is useful for subspace segmentation and motion tracking--

蓄电池的充放电控制策略，希望有点帮助哦。。。。。。。。(Charge and discharge control strategy of storage battery.Oh, I hope it helps)

关于蒙特卡洛法进行计算面积的，根据随机投点所得到的频率反推概率来求得面积。很好用的一种思维方法(About the Monte Carlo method to calculate the area, according to the random frequency of investment points to get the probability to obtain the inverse area. A good way of thinking with)

详细解释了ibatis的用法和jar包。。。。。。。。。。。。。(A detailed explanation of the use and ibatis jar package. . . . . . . . . . . . .)

MACH Kernel Implementation

fuzzy is a very useful technique in doing project works in the field of technology

MATLAB5.3精要、编程及高级应用。分三篇，基础篇为MATLAB的基本操作和功能；中级为数值计算和编程和simulink功能；高级为深入介绍simulink系统仿真方法；与信号处理、控制系统分析、系统仿真应用结合的书籍。(MATLAB5.3 essence, programming and advanced applications. Three points, Basics of MATLAB' s basic operations and functions intermediate for the numerical computation and programming and simulink function advanced systems for in-depth introduction simulink simulation and signal processing, control system analysis, system simulation applications with the books.)

This paper presents a new approach to image segmentation using Pillar K-means algorithm. This segmentation method includes a new mechanism for grouping the elements of high resolution images in order to improve accuracy and reduce the computation time. The system uses K-means for image segmentation optimized by the algorithm after Pillar. The Pillar algorithm considers the placement of pillars should be located as far from each other to resist the pressure distribution of a roof, as same as the number of centroids between the data distribution. This algorithm is able to optimize the K-means clustering for image segmentation in the aspects of accuracy and computation time. This algorithm distributes all initial centroids according to the maximum cumulative distance metric. This paper evaluates the proposed approach for image segmentation by comparing with K-means clustering algorithm and Gaussian mixture model and the participation of RGB, HSV, HSL and CIELAB color spaces.

It will perform the Zooming operation on input image.