chap9_1

首先介绍了VC ++ 6. 0 ,OpenGL 和MATLAB 6. 0 三种软件各自特点 其次在各自特点的基础上,建立了 基于三者相结合的自由飞行空间机器人仿真试验平台 最后以建立自由飞行空间机器人的运动仿真系统为例, 说明了该试验平台的优越性和有效性。(First introduced the VC++ 6. 0, OpenGL and MATLAB 6. 0 followed by three features of the software in their respective characteristics on the basis of the three based on a combination of free-flying space robot simulation platform in order to establish the final free-flying space robot movement simulation system as an example to show the superiority of the test platform and effectiveness.)

波束形成就是从传感器阵列重构源信号。（1）、通过增加期望信源的贡献来实现；（2）、通过抑制掉干扰源来实现。经典的波束形成需要观测方向(期望信源的方向)的知识。盲波束形成试图在没有期望信源方向信息的情况下进行信源的恢复(From sensor array beamforming is reconstructing source signal.(1), by increasing the expected source contribution to achieve (2), by suppressing interference sources.Classic beamforming need observation direction (expected source direction).Blind beamforming is trying to not expect source direction information of source of recovery)

利用MATLAB编程解决的在3端电源的条件下的故障测距的实现.(.T line of catching problems)

模糊神经网络解耦MATLAB程序，系统辨识中有用，希望对大家有帮助(Fuzzy Neural Network Decoupling MATLAB procedures, system identification useful, and they hope to help everyone)

说明：  用matlab做成的维纳滤波器程序，跟踪先验信噪比使用直接判决的方法进行滤波(Made use of the Wiener filter matlab program to track a priori signal to noise ratio using a direct method of filtering decision)

正确率可以达到98％，利用matlab写成的窄带噪声发生，使用高阶累积量对MPSK信号进行调制识别。( Accuracy can reach 98 , Using matlab written narrowband noise occurs, Using high-order cumulants of MPSK signal modulation recognition.)

用LCS方法解决字符匹配问题，用到动态规划的思想。原创(LCS solution with matching characters, the idea of using dynamic programming)

说明：  模糊聚类中的传统闭包法进行模糊等价矩阵的计算，中文解释清晰，可运行，是学习的好案例！(using this program to take fuzzy equilbrium matrix calculation, which is clear for learning fuzzy clustering.)

32阵元的MUSIC算法，基于特征空间分解，内有详细说明，供大家参考。(32 Element MUSIC algorithm, based on the decomposition of space, which is described in detail, for your reference.)

对仿真信号进行快速傅里叶变换，再进行经验模态分解，再对每个分量求FFT(Simulation signal fast Fourier transform, and then empirical mode decomposition, and then seek FFT for each component)