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MATLAB在天线方向图中的应用与研究文章(MATLAB in the antenna pattern in the application and research articles)

harris corner detector using Matlab

利用蚂蚁算法求解最短路径问题，稍作修改既可以用于移动机器人路径规划当中。(Ants use the shortest path algorithm to solve the problem, with some slight modifications can be used in mobile robot path planning among them.)

For beginner learning PID.Reproduce temperature PID control method using matlab.

matlab环境下的火箭外弹道质点方程的数值求解(4DOF of rockets exterior ballistic)

Matlab程序，计算Bayliss分布天线方向图。(Matlab program that calculates Bayliss distributed antenna pattern.)

对音频信号进行DWT变换，可嵌入水印信息(DWT transform audio signals can be embedded watermark)

一个非常有用的用遗传算法求解tsp的小例子，简洁易懂。(A very useful small example using genetic algorithms to solve tsp, concise and easy to understand.)

DTMB，全称Digital Television Terrestrial Multimedia Broadcasting。上述资料包含了最新标准，及链路级仿真matlab代码(Digital Television Terrestrial Multimedia Broadcasting)

各种方法的去噪程序 den1.m 使用半软阈值方法对图像进行去噪 den1_5_1.m 半软阈值的改进方法 对第一层重构图像进行均值滤波 den1_9.m 半软阈值的改进方法 将线性衰减的函数改为指数的 den1_10.m 半软阈值的改进方法 对第一层的重构图像再次进行小波阈值去噪 den2.m 用软硬阈值函数的改进方法进行去噪 den3.m 用广义阈值函数进行去噪 den4.m 用自适应特征阈值函数进行去噪 wdenoise.m 用Donoho阈值或Birge-Massart策略及软阈值或硬阈值函数进行去噪 meanfilter.m 均值滤波方法进行去噪(对比用) medfilter.m 中值滤波方法进行去噪(对比用)(Denoising procedures for various methods Den1.m using semi soft threshold method for image denoising The improved method of den1_5_1.m semi soft threshold for the first layer of the reconstructed image The improved method of den1_9.m semi soft threshold will be changed linear to exponential. The improved method of den1_10.m semi soft threshold for the first layer of the reconstructed image again for wavelet thresholding denoising Den2.m using the soft and hard threshold function to improve the method of denoising Den3.m using generalized threshold function for denoising Den4.m with adaptive feature threshold function for denoising Wdenoise.m with Donoho threshold or Birge-Massart strategy and soft threshold or hard threshold function for denoising Meanfilter.m mean filtering method for denoising (contrast) Medfilter.m median filtering method for denoising (contrast))