56881_210197_41912

说明：  这个是语音信号处理里面的基于MMSE的谱减法增强处理程序，此种方法是我见过消除噪声最好的！(This is the speech signal processing inside the MMSE-based spectral subtraction to enhance handling procedures, this method is the elimination of noise, the best I' ve ever seen!)

When doing optimization, GA algorithm was initially selected, but the instability of the GA (or local optimization) is really frustrating, before and after the resulting difference can at times reach more than 30 , at that time due to time reasons, I chose to optimize 1000 times, then the minimum value of the most optimal solution. Although the problems are solved, but an academic, this style of running is pretty embarrassing. So, I downloaded a GA-PSO algorithm, try using the combination of GA and PSO optimizing strategies, results algorithm issues, efficiency and good. I downloaded the original algorithm, there is a problem is that it is aimed at all upper and lower limits of the design variables are the same, so I modified the program and improvements, you can now deal with upper and lower limits of the inconsistency problem and fix the bug. Now, program modifications, and share, hoping to be useful to you

说明：  adaptative colntrol with luenberger observer

Scalp EA, very classic and practical, like friends can be learn about

说明：  基于负熵的盲源分离算法，可以用于语音的盲分离，提高语音信号质量。本代码中，对原始信号分别为正弦波，方波，和随机信号，通过高斯信道的混合矩阵，获得接收信号，并通过基于负熵的盲源分离算法分理处原始信号。PS：Matlab版本为2018Ra(The blind source separation algorithm based on negative entropy can be used for speech blind separation and improve the quality of speech signal. In this code, for the original signal, sine wave, square wave and random signal, the received signal is obtained through the mixture matrix of the Gauss channel, and the original signal is processed by the blind source separation algorithm based on negative entropy. PS: MATLAB Version 2018Ra)

遗传算法与模拟退火,粒子群算法的结合与比较实验.稍微修改就可以学习应用(Genetic algorithms and simulated annealing, particle swarm optimization algorithm and comparison with experiment. A slight modification can learn the application of)

应用维纳滤波法去噪，在图像的频率特征和附加噪声已知的情况下，采用wiener去卷积比较有效(Wiener filter denoising applications, the frequency characteristics of the image and additive noise of known cases, more effective use of wiener deconvolution)

This is an implementation of Particle Swarm Optimization algorithm using the same syntax as the Genetic Algorithm Toolbox, with some additional options specific to PSO. Allows code-reusability when trying different population-based optimization algorithms. Certain GA-specific parameters such as cross-over and mutation functions will not be applicable to the PSO algorithm. Demo function included, with a small library of test functions. Requires Optimization Toolbox.

说明：  《精通MTLAB最优化计算》第6章 无约束一维极值问题 源码(&quot The most proficient MTLAB Optimization&quot Chapter 6 one-dimensional extremum problem without constraint source)

图像去雾 matlab代码 最好的去雾算法 ( quwu matlab)