GMM-toolkit

Duchi and Singer [24] proposed a boosting method for multi-class classification problems by utilizing the structural sparsity of model parameters. They claimed that the method can be generalized for multi-task learning.

说明：  三维随机粗糙面，可修改其相关函数或均方高度等参数(Three-dimensional random rough surface, it can modify its associated functions or parameters such as mean square height)

通过matlab和C语言的联合编程实现了微波方面smith圆图的功能(Matlab and C language through the joint programming of the microwave aspects of the function chart smith)

surface plot for matlab

prim 最小生成树 代码 matlab平台使用(prim tree code matlab)

利用AdaBoost算法进行分类，该程序为matlab源码。(Classify using the AdaBoost algorithm.)

用前向差分算法解二维薛定谔方程 很值得参考(With the forward difference algorithm for solving two-dimensional Schr?dinger equation is worth considering)

brain connectivity toolbox,生成随机网络(brain connectivity )

使用matlab来对图像进行边缘检测的方法之一，便于在此基础上进行其他的功能的实现(Using matlab to the image edge detection methods, to facilitate this function based on the realization of other)

伽博同轴全息记录与再现。通过衍射计算完成光学同轴全息记录与再现过程的仿真，可以观察再现像的特点。(Bo coaxial holographic recording and playback.Completed through the calculation of the diffraction optical coaxial holographic recording and playback process simulation, can observe reproduce like characteristics.)