DTMF1

关于电磁波散射的时域有限差分法计算程序 很好的(a code about finite difference time domain method for electromagnetic waves scattering)

说明：  视频监控中，基于matlab的视频跟踪源代码(Video surveillance, video tracking based on source code matlab)

：通过对数字信号处理课程的改革，增加了DSP系统的设计和开发的课程，拓宽高校电子工程类专业学生在DSP方面的知识，进一步培 养他们的动手能力和创新能力。该课程实验中需要使用到初学者开发套件——美国1rI公司的TMS320C5402DSK。本文将重点介绍该DSK板的硬件体系，并且简要介绍了与该硬件体系相对应的CCS2．0限制版集成开发环境，并进一步讨论了在此套件基础上所开设的一系列DSP实验内容。(The course of design and development of DSP system is appended during the teaching reform of Digital Signal Processing．This course can expand the E．E．undergraduates’knowledge of digital signal processor．Therefor．their practical ability and innovation idea are enhanced．TS320C5402 developer start kit provided by Texas Instruments Company iS introduced in this paper．Its hardware structure and soft— ware development environment(Co de Co mposer Studio 2．0 limited)are discussed in details．The content of experiments based on this DSK iS presented furthermore)

说明：  实现利用高斯分布聚类，即完成em算法，直接在matlab上运行，可以作图直观显示（二维数据）(Achieve Gaussian distribution clustering, complete em algorithm, running directly on matlab, you can visualize mapping (two-dimensional data))

已知邻接矩阵求无向网络图度分布的MATLAB程序。(MATLAB program known distribution of the adjacency matrix)

说明：  MATLAB语言与控制系统仿真课件以及源码(MATLab language and Control System Simulink Course File and Code)

基于matlab的窗函数滤波器设计 kaiser 窗(Filter design onmatlab)

Learning Selenium in 6 Easy Steps

AFS （Axiomatic Fuzzy Set)理论，我们老师与澳大利亚的一个教授合写的，可可以说这个理论是他们原创的，一经发表了好几篇ＳＣＩ论文，文章里面有ｍａｔｌａｂ　的代码！(In this paper, we introduce the basic ideas and the results of AFS (Axiomatic Fuzzy Set) theory with some simple illustrative examples. All operations and the calculations for AFS theory could be implemented by the Matlab programs and functions whose applied methods are explained and original codes are listed in the Appendix.)

利用基于排序的邻域粗糙集算法对具有高维属性的元数据进行属性约简，删减多余的无关属性，避免模型的过拟合，提高模型预测精度和模型运算速度(The algorithm based on the ordered neighborhood rough set is used to reduce the attributes of the high dimension attributes, to eliminate the redundant irrelevant attributes, to avoid the over fitting of the model, and to improve the accuracy of the model prediction and the operation speed of the model)