MV-S100649-00H_88E1111_Datasheet

Mixed control strategy of a doubly fed induction machine

波达方向（DOA） 估计的基本问题就是确定同时处在空间某一区 域多个感兴趣的信号的空间位置(即多个信号到达阵列参考阵元的方 向角)。最早的也是最经典的超分辨率(DOA)估计算法是著名的多信号 分类（Multiple Signal Classification） 法,简称 MUSIC 算法,它是 一类经典的基于特征结构分析的空间谱估计方法。该算法利用了信号 子空间和噪声子空间的正交性,构造空间谱函数,通过谱峰搜索,检测 信号的 DOA。(The basic problem of DOA estimation is to determine the simultaneous location in a certain region of space. Spatial position of multiple interested signals in the domain (i.e. the direction of multiple signals reaching the array reference elements) Directional angle). The earliest and most classical super-resolution (DOA) estimation algorithm is the well-known multi-signal.Multiple Signal Classification, referred to as MUSIC algorithm, is A classical spatial spectrum estimation method based on eigenstructure analysis. The algorithm utilizes signals. The orthogonality of subspace and noise subspace, the construction of spatial spectral function, through peak search, detection DOA of signal.)

matlab语言，用语保存数据，具体的save用法(matlab language, language save data, save a specific use)

matlab灰色模型程序，关于水压程序。(matlab gray model)

Different ratios of AR to the SE for a set of problem

使用MATLAB实现主成分分析，可以去除数据间的共线性及对大量数据进行降维处理。(Using the matlab to realize the principal component analysis to remove the liner of the date and reduce the dimension of the large amont of the date. )

MCMC方法主要是为了解决有些baysian推断中参数期望E(f(v)|D)不能直接计算得到的问题的。 其中v是要估计的参数，D是数据观察值(The concept consists of two parts:markov chain and monte carlo integration。)

利用高斯核自行完成高斯平滑。 1.gkernel.m: 创建高斯核。 2.getnorm.m: 将高斯核归一化以求得该核的图像 3.convo.m：不用自带函数求卷积 4.conducting.m: 举例执行程序(1.gkernel.m: Buidling Gaussian kernels. 2.getnorm.m: Normalizing Gaussian kernel in order to display the kernel. 3.convo.m: calculating the convolution. 4.conducting.m: conducting the program with some examples.)

MATLAB has a wide variety of functions useful to the genetic algorithm practitioner and those wishing to experiment with the genetic algorithm for the first time. Given the versatility of MATLAB’s high-level language, problems can be coded in m-files in a fraction of the time that it would take to create C or Fortran programs for the same purpose. Couple this with MATLAB’s advanced data analysis, visualisation tools and special purpose application domain toolboxes and the user is presented with a uniform environmentwith which to explore the potential of genetic algorithms.

matlab与c混合编程MEX的几个示范程序(matlab and C mex)