meilinmatlab

说明：  MATLAB图像处理源程序3：程序代码说明 P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩 P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 P0305：模拟图像受高斯白噪声和椒盐噪声的影响 P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 P0308：图像的自适应魏纳滤波 P0309：运用5种不同的梯度增强法进行图像锐化 P0310：图像的高通滤波和掩模处理 P0311：利用巴特沃斯（Butterworth）低通滤波器对受噪声干扰的图像进行平滑处理 P0312：利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理(MATLAB image processing source code 3: Procedure Code Description P0301: digital image data matrix display and Fourier Transform P0302: two-dimensional discrete cosine transform image compression P0303: using gray transform method to enhance the contrast of the image P0304: histogram equalization P0305: Simulation images by white Gaussian noise and Impulse noise impact P0306: 2D median filtering of function medfilt2 on the Salt and Pepper noise image filtering P0307: MATLAB functions filter2 mean filtering the noise in the image P0308: Image Adaptive Filter Weiner P0309: use five different gradient Enhancement Act for image sharpening P0310: the image of the high-pass filtering and mask handling P0311: use Butterworth (Butterworth) low-pass filter on the noise in the image smoothed P0312: use Butterworth (Butterworth) high-pass filter for image sharpening)

fxlms基本算法在有源噪声控制中的应用，有MSE曲线图(The application of basic FXLMS algorithm in active noise control has MSE curve.)

带Simth补偿的模糊PID控制器设计及仿真(Simth compensation with the fuzzy-pid controller design and simulation)

MMA盲均衡算法，上传供交流，希望大家提供宝贵的意见(MMA blind equalization algorithm, uploads for the exchange, we hope to provide valuable advice)

计算地震波的震中距和走时的的子程序，非常好用的子程序(Subroutine to calculate seismic epicentral distance and travel time, and very easy to use subroutines)

the file is for light

带阻滤波程序，直接运行即可，保证可用。注意:目录的设置一定要正确(Band-stop filter program can be run directly, to ensure that available. Note: The directory must be correctly set)

[hao]超宽带通信系统的Simulink仿真实现,较好的利用了matlab平台([hao] Ultra-Wideband Communication Systems Simulink simulation of the realization of a better platform to use the matlab)

说明：  无线通信基础，MIMO必读，MIT研究生教材，英文原版 (Wireless communications infrastructure, MIMO must-read, MIT graduate student teaching, the English original)

基于稀疏变量的欠定盲源分离，可以解决源数大于传感器数的问题，即欠定盲源分离问题。(Based on the sparse variable underdetermined blind source separation, can solve the source number is greater than the number of sensors the problems, i.e. underdetermined blind source separation.)