案例一 GUI数据传递和多窗口编程

多天线中的实现迫零检测算法和mmse算法的blast检测算法(Realize multi-antenna in the Zero-Forcing and MMSE detection algorithm algorithm blast detection algorithm)

my papers for LDA PCA for reference purpose

matlab code for solving 8Queens by GA algorithm

It is a tutorial on MatLab

matlabr软件应用的图形图像处理，很专业的教材，事例很多(matlabr graphic image processing software applications, very professional materials, many examples)

Least Mean Square Newton Algorithm

反应扩散方程 捕食者捕食模型 HOlling模型(Reaction-diffusion equation model of predator prey model HOlling)

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)

一个很好的学习图像处理的函数的例子程序，对于初级学习者来说，有很好的帮助，对于初学习者非常适合！(a good learning image processing function examples procedures for primary learners, good help, very suitable for early learners!)

谱分析 绘制瞬时包络图和瞬时频率图 绘制Hilbert-Huang谱 画出边际谱(Spectrum draw instantaneous envelope and instantaneous frequency diagram drawing Hilbert-Huang spectrum shown marginal spectrum)