AL-A-Resumo-02-EspacosVetoriais

PCA程序，用于信号的主分量分析，用过几次，感觉不错(PCA program, the main component for signal analysis, used a few times, I feel good)

jabber source code c#

三维数字滤波器中的高斯理想低通滤波器的matlab仿真及其结果(3 d digital filter of gaussian ideal low-pass filter matlab simulation and the result )

这是斯坦福大学的教授研制的软件，中国现在学习用的很广的工具，我给出的是相关的资料文章。(This is a professor at Stanford University, developed software, China is now very widely used learning tools, I give the relevant information in the article.)

随机自动分班级排学号软件 一个朋友在中学教书，经常为排班级排学号头痛，于是做了这么一个小软件让朋友用用，反馈感觉上还不错。 本软件适用于小学升初中只有两科成绩,且成绩只有A,B,C三个标号. 说明一下:该随机自动分班级排学号软件, 不仅有有考虑到,成绩的均匀, 还考虑到生源地(即原毕业学校),性别,及班级学生个数的均匀. 一般来说,每个班级的总体都比较均匀 具体的说明，可以运行一下本软件，点一下生成源文件样本，然后参考一下即可。(Random Automatic Class scheduling software school No. A friend of mine to teach in secondary schools, often for the Class Pai Pai Student headache, then to do so, a small software that allows friends to use, and feel pretty good feedback. This software applies to primary and junior high school only two subjects, and the results only A, B, C grade three. Explain: The random Automatic Class No. Pai school software, not only has to take into account, results in uniform, but also taking into account the students (ie the original graduate schools), gender, and class number of the uniform. Generally speaking, each Class are relatively uniform overall specific, you can run like the software, click the source file to generate samples, and then reference click.)

这里面汇总了matlab局部放大的三种方法，可以对matlab中plot进行局部放大，带程序。(It mainly is concerned about the magnification of plot.The users can use it to magnify what they want.)

MATLAB对数字信号进行均值滤波，尤其是对数字图像(MATLAB for digital signals mean filter, especially for digital images)

一个二维的fdtdc++编写的程序，较完整，带有pml边界条件。感兴趣的可以下载看看。(A two-dimensional fdtdc++ preparation procedures, more complete, with pml boundary conditions. Interested can download to see.)

GM 862 gsm gprs modul visual basic project and aplication. Take photo from GM 862 modul and sample project.

A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the `empirical mode decomposition method with which any complicated data set can be decomposed into a nite and often small number of `intrinsic mode functions that admit well-behaved Hilbert transforms. This decomposition method is adaptive, and, therefore, highly ecient.