apiext

说明：  图像压缩去噪增强锐化程序，供大家参考。 包括：数字图像矩阵数据的显示及其傅立叶变换 二维离散余弦变换的图像压缩 采用灰度变换的方法增强图像的对比度 采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 图像的自适应魏纳滤波 运用5种不同的梯度增强法进行图像锐化 图像的高通滤波和掩模处理 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 利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理-(Sharpen Image Compression Denoising enhanced procedures for your reference. Include: digital image data display matrix and its Fourier transform two-dimensional discrete cosine transform image compression method using gray-scale transformation of the contrast-enhanced images using two-dimensional median filter function by medfilt2 of salt and pepper noise image filtering using MATLAB The function affected by noise interference filter2 images mean filter Adaptive Image Filtering Wehner use five kinds of different gradient method to enhance image sharpening images of high-pass filtering and mask treatment using Butterworth (Butterworth) low pass filter noise by smoothing the images deal with the use of Butterworth (Butterworth) high-pass filter for sharpening images treatment)

说明：  code to test the mimo system for the ML and MZ

单纯形法，求解线性规划问题的通用方法。这里给出其Matlab源程序(Simplex method for solving linear programming problems common method. Here are its Matlab source)

实现随机信号序列的QPSK调制和相干解调，观察信号的星座图，计算误比特率和误码率。(this code is designed for the signal s QPSK modulation and demodulation exactly. Meanwhile, the BER and SER were estimated and drawed.)

说明：  Multirate滤波器设计。模拟带通信号频率范围1KHz—1.1KHz，设计一个采样频率8KHz数字频谱分析系统，要求频率分辨率0.1Hz。(Multirate filter design. Analog bandpass signal frequency range 1KHz-1.1KHz, design a sampling frequency of 8KHz digital spectrum analysis system, required frequency resolution of 0.1Hz.)

求根music算法+最小范数music算法 DOA估计(music algorithm)

matlab 中用来将rgb数据转换成灰度图像的源代码(matlab used to the rgb data into gray-scale image of the source code for)

这是一个实值的Noiselet变换，压缩感知的图像应用中的的Noiselet观测矩阵 (1) This implementation uses exactly m*log2(m) additions/subtractions. 2) This is a real-valued variation of "dragon" noiselets. 3) This is symmetric and orthogonal. To invert, apply again and divide by m.)

verification data is numbers only

Boundary element method function [index,g,h,a,unb,x,u,un,uin]=bemlabecom(n,c,index,in,cin) [index,g,h,a,unb,x,u,un,uin]=bemlabecom(16,[0 0 0.25 0 0.5 0 0.75 0 1 0 1 0.25 1 0.5 1 0.75 1 1 0.75 1 0.5 1 0.25 1 0 1 0 0.75 0 0.5 0 0.25 0 0],[1 0 1 0 1 0 1 0 0 200 0 200 0 200 0 200 1 0 1 0 1 0 1 0 0 100 0 100 0 100 0 100],9,[0.25 0.25 0.50 0.25 0.75 0.25 0.25 0.50 0.50 0.50 0.75 0.50 0.25 0.75 0.50 0.75 0.75 0.75]) in bemlabecom2 we change a & unb to : a1 a2,unb1 unb2 n=number of nodes=number of element=number of point c=matrix that determine the coordinate of point m=coordinate of nodes in global coordinates index: determine u or un for boundary nodes in:number of internal nodes cin: coordinate of internal nodes