Rayleigh-in-Transmit-beamforming

MATLAB智能算法30个案例分析 源代码 有各种智能算法，如遗传算法，免疫算法，神经网络的实现(Intelligent algorithm MATLAB source code 30 case studies have a variety of intelligent algorithms, such as genetic algorithm, immune algorithm, neural network implementations)

基于matlab软件实现等距离离散化为粗糙集约简前准备(matlab Equidistance discretization)

This document contain a model of wi-fi 802.11 b Its great work

IEEE57节点电力系统标准参数和潮流数据(IEEE57 node power system standard parameters and trend data)

这是一个关于语音信号处理方面的程序，以前做毕业设计的时候在网上收集的，希望对大家有用。(This is a program about the speech signal processing, when done before graduation online collection, we want to be useful.)

ovsf码的编程算法， matlab实现， 可以直接使用(ovsf matlab)

The C Programming Language

这个是一个HHT的镜像延拓的emd程序。可以适当地解决emd变换的端点效应问题。你可以下下来参考下。(This is a mirror image of HHT emd Extension program. Emd can transform an appropriate solution to end effects. You can refer to the next down.)

最优信息法，有序样品聚类——最优分割，采用多种分割方法 (Optimal information method, ordinal clustering- the best split, using a variety of segmentation methods)

实现了 SVM 在医学图像分类中的应用，通过医学图像的实验结果验证了该方法的有效性。 对 SVM 算法进行了深入研究，结合量子行为的粒子群算法的优点，提出了一种量子行为的粒子群算法和 SVM 结合的混合分类模型，应用于医学图像的分类中。 深入研究了 K-means 算法，结合了无监督聚类和监督分类方法的优点，提出了一种 K-means 和 SVM 结合的混合分类模型，并应用于医学图像的分类中。 利用粒子群和量子行为的粒子群算法对 K-means 算法进行了改进，并将改进的K-means 算法与 SVM 算法结合形成全自动分类模型，并且把它应用于医学图像的分类中。 (SVM in the classification of medical image applications, medical images through the experimental results verify the effectiveness of the method. SVM algorithm conducted in-depth research, combined with the quantum behavior of the advantages of particle swarm optimization, PSO and SVM combined behavior of a quantum mixed classification model, applied to medical image classification. In-depth study of the K-means algorithm combines the advantages of unsupervised clustering and supervised classification method, propose a hybrid combination of a K-means and SVM classification model, and applied to the classification of medical images. Improved particle swarm algorithm using particle swarm and quantum behavior of the K-means algorithm, and improved K-means algorithm and SVM algorithm combined with the formation of a fully automatic classification model, and apply it to medical image classification.)