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example of matlab,optimization method which is used with different model.it will be useful for whom they want to learn Matlab by themselves1

MIMO下的ZF滤波器的实现，主要实现的功能是针对任意大小的收发天线的误比特率仿真(MIMO ZF filter is implemented under the main function is to achieve any size for the antenna simulation of bit error rate)

说明：  该书的英文版是国外电子信息类优秀教材，国内外很多学校采用它作为教材，基本上是学习matlab的经典和权威书籍了，但是中文修正版没有（虽然是网友自己翻译的），但还不值得一看的。(The English version of the book is the best type of foreign electronic information materials, both at home and abroad, many schools use it as teaching material, is basically a classic learning matlab and authority of books, but there is no Chinese version of the amendment (although the users own translation), but also not worth a visit.)

用matlab实现三次NURBS插值曲线拟合，插值源程序(Using matlab to achieve Cubic NURBS interpolation curve fitting, interpolation source)

功率谱密度计算程序，可以用于计算时域信号的功率谱密度。(The power spectral density calculation procedures can be used to calculate the power spectral density of the time-domain signal.)

All of these matlab files deal with SFBC/STBC. i,e transmit diversity. Additionally, 2x2 ZF channel estimation is demonstrated. Also MMSE channel estimation in Rayleigh fading environment is demonstrated.

该代码利用matlab，根据各类边界条件的设定，实现了FDTD的算法。( This MATLAB M-file implements the finite-difference time-domain solution of Maxwell s curl equations over a three-dimensional Cartesian space lattice comprised of uniform cubic grid cells.)

这些录音由Thorsten Zander，柏林，和蔼可亲地提供；如果你使用这些录音的出版物，请引用： 赞德，T. O.，Kothe，C.，Jatzev，S.＆Gettne，M（2010）。增强人机交互与主动和被动脑机接口的输入。在大脑-计算机接口中（181-199页）。斯普林格伦敦。(These recordings were kindly provided by Thorsten Zander, TU Berlin; if you use these recordings for a publication, please cite: Zander, T. O., Kothe, C., Jatzev, S., & Gaertner, M. (2010). Enhancing human-computer interaction with input from active and passive brain-computer interfaces. In Brain-Computer Interfaces (pp. 181-199). Springer London.)

以前下载的一些用matlab编写的关于运动轮廓模型程序(Previously downloaded some prepared using matlab contour model on the campaign process)

has provided the primary evidence supporting involvement of the dopaminergic system in the pathology of RLS. While PET and SPECT imaging of the striatum held initial promise of linking dopamine abnormalities to RLS, they have failed to reveal a consistent pattern of abnormalities. The dopamine-2 receptor binding potentials of RLS patients have been