GMKL-matlabcode

二进制编码的简单遗传算法源程序，很完整，适合初学者学习。(A simple binary encoding genetic algorithm source code, is very complete, suitable for beginners to learn.)

混沌的判断指标Lyapunov指数计算,是小学期课程设计的题目，添加噪声处理。( Chaos indicator for Lyapunov index calculation, Is the topic of the elementary school stage curriculum design, Add noise processing.)

ARMA模型的功率谱估计程序，简单易懂，免费下载。(spectral estimation)

是一个关于OFDM仿真的小程序，比较小的程序，可以拿来练练手(It is a little on the OFDM simulation program is relatively small program that can be used to practice your hand)

说明：  将白噪声和瑞丽分布的噪声模拟为信号的背景噪声，分别通过小波去噪，EMD去噪，EMD结合小波去噪的方法来进行背景噪声去噪分析。(Ruili, the distribution of white noise and the noise modeled as background noise signals, respectively, through the Wavelet denoising, EMD denoising, EMD combined with wavelet denoising approach to denoising of background noise.)

this is a codeto detect voice or unvoice specch

数字图像修复算法的评价标准也是从两个方面进行评价的，一个是修 复算法的效率，一个是修复后图像质量。修复算法的效率主要就是看修复 图像所用的时间，可以用时间就行量化。而图像质量很难从量上唯一的进 行评价，目前图像修复质量还没有统一的评价标准，从实际应用出发，修 复后图像质量的好坏大多数是从以下两个方面就行评价，修复后图像给人 主观上的“满意度”和客观上图像的cnr、enl、epi、psnr、snr来评判。(The evaluation criteria of digital image restoration algorithms are also evaluated from two aspects, one is repair. One of the efficiency of complex algorithm is the image quality after restoration. The efficiency of the repair algorithm depends mainly on the repair. The time spent on the image can be quantified in terms of time. But image quality is difficult to improve quantitatively only. At present, there is no uniform evaluation criterion for image restoration quality. Starting from practical application, repair The quality of restored images is mostly evaluated from the following two aspects, and the restored images are given to people. Subjective "satisfaction" and objective image cnr, enl, epi, psnr, SNR to judge.)

matlab生成随机数，uinform产生一组[0，1]分布的随机数，riddling产生一个N(0,1)正态分布随机数，normal产生n个N(a,b)正态分布随机数。(Use matlab to generate random numbers, uinform produce a set of [0,1] random number distribution, riddling produce a N (0,1) normally distributed random numbers, normal generate n N (a, b) normally distributed random numbers.)

截断的核范数，可用于矩阵恢复。需要知道丢失点的像素位置。该算法是 2013 PAMI上一篇文章里的算法。感兴趣的看看(Nuclear norm truncated matrix can be used for recovery. Need to know the pixel positions lost points. The algorithm is an article on the 2013 PAMI algorithms. Look interested)

student who required matlab code