Engineering_Optics_with_MATLAB

运用支持向量机进行分类，可以帮助你更好的了解支持向量机如何利用工具箱进行分类(Support vector machines for classification, can help you better understand how to use the Toolbox support vector machine classification)

MATLAB CODE FOR INFORMATION THEORY AND CODING

对DOA进行估计的一种较好的方法，能精确地对参数进行估计(Of the DOA estimate of a better way to accurately estimate the parameters)

快速掌握matlab的书籍.matlab实例编程一百个源程序(Quickly learn matlab books. Matlab source code examples of programming 100)

2009年9月全国大学生数学建模获奖论文所需程序代码，其中有较详细的matlab编程，应该有些用处吧(September 2009 Mathematical Contest in Modeling program code required for the award-winning paper, including more detailed matlab programming, it should be useful)

采用多孔trous算法(undecimated wavelet transform)实现小波变换 (The use of porous trous algorithm (undecimated wavelet transform) the realization of wavelet transform)

plotting planes for matlab

Navier_Stokes_simulation 是NS方程的数值模拟很好的实例。对于N_S方程很感兴趣的人可以借鉴参考(Navier_Stokes_simulation NS equation numerical simulation is a good example. For those who are interested in N_S equation can draw reference)

双基地MIMO雷达系统DOA和DOD联合估计的MATLAB仿真程序，系统架构和算法可参考以下两篇原始文献。 Haidong Yan,Jun Li, Guisheng Liao.Multi-Target Identification and Localization Using Bistatic MIMO Radar Systems.(cited by 106)EURASIP Journal on Advances in Signal Processing , vol.2008, Jan. 2008. Ming Jin,Guisheng Liao,Jun Li. Joint DOD and DOA Estimation for Bistatic MIMO Radar. Signal Processing, vol.89,no.2,pp:244-251,Feb.2009(MATLAB simulation program for bistatic MIMO radar DOA and DOD estimation. Please refer the following papers for further information of the bistatic MIMO radar systam and corresponding algorithm. Haidong Yan,Jun Li, Guisheng Liao.Multi-Target Identification and Localization Using Bistatic MIMO Radar Systems.(cited by 106)EURASIP Journal on Advances in Signal Processing , vol.2008, Jan. 2008. Ming Jin,Guisheng Liao,Jun Li. Joint DOD and DOA Estimation for Bistatic MIMO Radar. Signal Processing, vol.89,no.2,pp:244-251,Feb.2009)

利用八组故障样本数据，根据样本的特征利用SOM网络进行故障诊断。(Using the eight groups of fault data samples, according to the characteristics of the sample using SOM network fault diagnosis.)