NSGA2

模式识别中的最近邻算法用matlab实现，简单易懂，并做了实验，用图像表示聚类结果。(The nearest neighbor algorithm for pattern recognition with matlab implementation, simple to understand, and do the experiment, with images that clustering results.)

LDA是人脸识别中比较基础的一个算法，在人脸识别中使用较广(Comparison of LDA in face recognition are based on an algorithm used in face recognition broader)

神经网络图像处理程序，可以实现入门级功能(Neural network image processing procedures, entry-level functions can be achieved)

this code is about tabu search optimization....

三相电压源型逆变器的滞环跟踪PWM的simulin模型，我使用的是matlab2012a(current lagloop tracking PWM inverter)

Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others. Serious students are directed to the sources listed below for a theoretical description of the algorithm. KF Lee (2) offers an especially good tutorial of how to build a speech recognition system using hidden Markov models.

THE ZIP FILE CONTAINS ALL THE PROGRAMS OF A BOOK NEURAL NETWROK FOUNDATIONS BY SATISH KUMAR

说明：  matlab在电力系统中的应用，基于UPFC仿真程序(matlab in power system applications, based on UPFC simulation program)

调制识别是非协作通信中的关键技术之一，在电子对抗、软件无线电等领域 应用十分广泛。该过程介于信号检测与解调之间，由于对传输信号没有过多的先 验信息以及在接收端有很多未知的参数，例如：信号功率，载波频率和相位偏移， 时间信息等，导致对调制方式的盲识别是一项很困难的任务。此外，实际中存在 多径衰落、频率选择性和时变信道等问题，使得这项任务变得更具有挑战性。 (The modulation recognition is one of the key technologies of the non-cooperative communication, such as electronic countermeasures and software defination radio, therefore it is such a significant discipline and orientation in the research of communication field. Obviously, without enough knowledge in transmitter and verified parameters about receivers, for example signal power, carrier frequency and phase offsets and so force, it is hard to get the modulation of blind identification. What is more, for the sake of the multipath fading, frequency-selective and time-varying channels in the real scenarios the task is even harder. )

1.将BMP图像内容读入内存数组。 2. 调整图像的灰度，对图像进行灰度变换（反变换）。 3. 对图像进行较正,分别取值为0.4,0.6,0.8.(1. The BMP image content is read into memory array. 2 Adjust the gray image, the image gray-scale transformation (inverse transform). 3 more positive image, respectively, the value of 0.4,0.6,0.8.)