ReadFID

详细讲解了matlab中PDE工具箱的应用,附有具体的例子并附图说明()

加算方法中的追赶法的例子，例子经过了最优化处理，可以最小开销的实现追赶法(Add count method to catch up with examples of law, for example, has been optimized to deal with, you can catch up with the realization of the minimum cost method)

上传几个关于线阵RLS算法、圆阵LMS算法、矩形波以及SNR的matlab源代码，都可以出图，希望对大家有用！(From a few RLS algorithm on the linear array, circular array LMS algorithm, as well as the SNR of the rectangular wave matlab source code, can be a diagram, useful for all of us hope!)

卡尔曼滤波和扩展卡尔曼滤波Matlab源程序，广泛用于参数估计，滤波去噪，惯性导航等应用方面。(Kalman filter and extended Kalman filtering Matlab source, widely used in parameter estimation, filtering noise, inertial navigation and other applications.)

画出下述情况下均匀线阵方向图 1）计算来波方向为0度方向图 2）画出来波方向为45度时的方向图 3）画出来波方向为0度，幅度取分贝数：20log***（单位为dB）时的方向图 4）画出来波方向为0度，随着阵元数的增加，当N=16，N=32时的方向图，并对方向图的变化情况进行说明(Draw the following conditions uniform linear array 1) calculation of wave direction is 0 degrees direction diagram 2) draw out the wave direction is 45 degrees direction map 3) draw out the wave direction is 0 degrees, and amplitude decibels: 20log*** (unit dB) when the direction of FIG. 4) draw out the wave direction is 0 degrees, with the increase of the number of array elements, when N=16, N=32 pattern, and the change of direction is described )

matlab 的s函数应用心得，介绍了s函数的用法(matlab s-function application of experience, describes the use of the function s)

在程序中用一般的MUSIC方法估计了信号的频谱，从两图中可看出在信号各频率处，频谱的峰值较大，故能明显的与噪声相区别，可在一定程度上避免在信号幅度较小时信号被噪声淹没的情况。(MUSIC method general procedures used to estimate the spectrum of the signal, it can be seen from the two graphs in the signal at each frequency of the spectrum peak larger, and it could be significantly distinguished from noise in the signal can be avoided to some extent a lesser extent, the signal is noise submerged.)

数字滤波器设计文档(自己作设计时用的ppt)(Digital Filter Design Documents (for their design of ppt))

triangle-Mesh generation- FEM-electromagnetic

扩展卡尔曼滤波算法用matlab实现。分别计算出观测值和卡尔曼滤波值进行对比。(Extended Kalman filter algorithm using matlab implementation. Observed values were calculated values were compared and Kalman filtering.)