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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(Code Description P0301: digital image data display matrix and Fourier transform P0302: Two-dimensional discrete cosine transform image compression P0303: gray-scale transformation method using the contrast enhanced image P0304: Histogram of homogenization P0305: simulated images by Gaussian white noise and salt and pepper noise of P0306: two-dimensional median filter function medfilt2 on the image noise by filtering salt and pepper P0307: using MATLAB in the function filter2 noise on the image by mean filter P0308: Image Adaptive Weiner Filter P0309: the use of 5 different gradient enhanced image sharpening method P0310: the image of the high-pass filter and mask treatment P0311: Using Butterworth (Butterworth) low pass filter the image noise by smoothing P0312: Using Butterworth (Butterworth) high pass filter sharpening the image)

These are MATLAB codes for implementing Chebyshev-Type 2 Bandpass and Bandstop filters.

An Experimental Investigation of SIMO, MIMO, Interference-Alignment (IA) and Coordinated Multi-Point (CoMP)

此程序主要是基于希尔伯特-黄变换编写的MATLAB程序，用于搞科研的工作者们。(This program is mainly based on Hilbert- Huang Transform written MATLAB program for workers who engage in scientific research.)

使用支持向量机进行特征选择的集成算法模型(Feature selection of support vector machines)

说明：  KL变换，matlab实现，可以继续修改。(KL transform, matlab realize, you can continue to modify.)

两个rbf 源程序，只要填入输入输出数据就可以用(two rbf Source program )

MATLAB-SIMULINK通信系统建模与仿真实例分析(MATLAB-SIMULINK communications system modeling and simulation analysis)

振动信号在进行处理之前，需要将信号进行一系列处理以便于进行数字分析(Before processing the vibration signal, the signal needs to be processed to a series of digital analysis of the)

说明：  一种基于稀疏信号恢复的DOA估计方法，CS采用L1SVD方法进行信号恢复(A DOA estimation method based on sparse signal recovery is proposed. CS uses L1SVD method for signal recovery.)