基于空间飞行器的姿态仿真程序-MATLAB源代码

本程序基于Matlab，可以对特定波长光线在透镜系统中进行光线追迹。可以生成任意方向平行光，点光源任意角度光线，并对全反射，光线射出系统等特殊情况用红色标出。透镜数任意，透镜参数可设。(The program is based on Matlab, with a specific wavelength of light in the lens system for ray tracing. Parallel light can be generated in any direction, at any angle point source of light, and the reflection of light injection system and other special circumstances marked in red. Any number of lenses, lens parameters can be set.)

说明：  基于MATLAB的BP神经网络非线性映射能力实现图像压缩。(MATLAB Based on BP neural network nonlinear mapping capability for image compression.)

本例程为改进的LMS算法NLMS算法的MATLAB实现和其收敛性的验证程序(This routine is improved LMS algorithm NLMS algorithm in MATLAB and its convergence verification procedures)

将改进的粒子群算法和GA与SVM相结合，通过参数寻优构建新模型完成对空气质量指数的预测(The improved particle swarm optimization and genetic algorithm are combined with SVM. The prediction of air quality index (AQI) is completed by constructing a new model by parameter optimization.)

采用matlab实现正交频分复用技术，用于各种现代数字处理中。(Using matlab to achieve orthogonal frequency division multiplexing, for a variety of modern digital processing.)

说明：  基于Matlab的扩频高度表捕获跟踪算法软件仿真(Matlab-based spread-spectrum acquisition and tracking algorithm for software simulation altimeter)

MAGNETIC SUSPENSION USING MATLAB

music高阶谱分析算法，采用加权网络中节点强度和权重都是幂率分布的模型，gmcalab 快速广义的形态分量分析，自己编的5种调制信号，表示出两帧图像间各个像素点的相对情况，有详细的注释，有小波分析的盲信号处理，车牌识别定位程序的部分功能。( music higher order spectral analysis algorithm, Using weighted model nodes in the network strength and weight are power law distribution, gmcalab fast generalized form component analysis, Own five modulation signal, Between two images showing the relative circumstances of each pixel, There are detailed notes, There Wavelet Analysis Blind Signal Processing, Part of the license plate recognition locator feature.)

matlab的FDC工具箱，对飞控系统很有帮助。(matlab the FDC toolbox of helpful flight control system.)

本文提出的中值滤波的快速算法的基本思想是：原始数据序列上中值滤波的滑窗在移动过程中，当前窗只要删除其最早的元素，加入窗后的新元素，即成为下一窗的内容。这个只是Matlab里封装的算法代码(In this paper, the median filtering of the fast algorithm for the basic idea is: the original data sequence in the sliding window filtering process in the mobile, the current window as long as the deletion of its first element, adding a new element after the window, that is, the next window content.)