mimo

说明：  关于UMHexagonS方式的一些论文，使用CAJviewer阅读(UMHexagonS)

Program to analize diferent transfer functions and looking for changes on it varying the gain K.

计算米氏散射专业程序。做散射等必须的算法.欢迎下载使用(Mie scattering calculations professional procedures. The algorithm must be scattering. Welcome to download)

说明：  在盲信号处理过程中，通过该算法实现信号分离(Blind source seperation)

Programming Exercise

在采样点之间的频率响应是由各采样点的加权内插函数叠加而形成的，因而有一定的逼近误差。该误差大小取决于理想频率响应的形状，理想频响特性变化越平缓，内插值越接近理想值，逼近误差越小；反之，如果采样点之间的理想频响特性变化越陡，则内插值与理想值之间的误差越大，因而在理想滤波器不连续点的两边，就会产生尖峰，而在通带和阻带就会产生波纹。用频率采样法设计的实际滤波器频率响应如图1所示。由图1可知，实际滤波器的阻带衰减取决于内插函数第一旁瓣幅度值的大小，其大小决定了所设计的滤波器的阻带性能。(Interpolation function superimposed between sampling points of the frequency response is weighted within each sampling point and the formation of, and thus have a certain degree of approximation error. The size of this error depends on the shape of the ideal frequency response and the ideal frequency response characteristic change is more gentle, interpolated and more close to the ideal value, the smaller the approximation errors Conversely, if the sampling point between the ideal frequency response characteristics of the steeper the change, and then the interpolated the larger the error between the ideal value, and thus in the ideal filter both sides of the discontinuity point, will produce spikes occurs ripple in the passband and stopband. Actual design frequency sampling filter frequency response is shown in Figure 1. Figure 1 shows, the actual filter stopband attenuation depending on the interpolation value of the size of the first side-lobe amplitude of the function that determin)

使用Python编写的AI程序Pacman，可以适合AI的初学者，有BFS, DFS, UCS, A Star 运行的命令在commands.txt文件里 可以用 bash commands.txt演示(AI programs written in Python Pacman, AI can fit beginners, there BFS, DFS, UCS, the command runs in commands.txt A Star file can bash commands.txt demo)

通过学习此程序可以了解相关方面的语言结构，对于编程参考和借鉴有很大的实际意义，肯定有很大的帮助(Chinese verification code)

信号处理，用这个Matlab的程序可以处理信号。(filter signal)

MMAdapGA:用多变异位自适应遗传优化求解一维无约束优化问题 (MMAdapGA: with changeable ectopic adaptive genetic optimization solution of one-dimensional unconstrained optimization problems)