matlab-examples

[matlab在数学建模中的应用]一书源代码( "Matlab mathematical modeling," a book source code)

非常详细的MS3110技术手册,MS3110是一款微小电容检测芯片，可以检测0-10pF电容(MS3110 technical manual is very detailed)

感知器感知器算法训练二元线性分类器。结构体数据使用感知器学习规则 找到给定的二分类标签数据超平面。 (PERCEPTRON Perceptron algorithm to train binary linear classifier. Synopsis: model = perceptron(data) model = perceptron(data,options) model = perceptron(data,options,init_model) Description: model = perceptron(data) uses the Perceptron learning rule to find separating hyperplane from given binary labeled data. model = perceptron(data,options) specifies stopping condition of the algorithm in structure options: .tmax [1x1]... maximal number of iterations. If tmax==-1 then it only returns index (model.last_update) of data vector which should be used by the algorithm for updating the linear rule in the next iteration. model = perceptron(data,options,init_model) specifies initial model which must contain: .W [dim x 1] ... normal vector. .b [1x1] ... bias of hyperplane. .t [1x1] (optional) ... iteration number. Input: data [struct] Labeled (binary) training data. .X [dim x num)

In this paper, we consider a coded cooperation diversity scheme that is suitable for L-relay channels that operate in the decode–forward mode. The proposed scheme is based on convolutional coding, where each codeword of the source node is partitioned into two frames that are transmitted in two phases.

phase_shift_deadtime.rar,功率电子领域matlab仿真文件，已经验证过，程序运行正常(phase_shift_deadtime.rar,Power electronics field matlab simulation file, has already been verified, the normal operating procedures)

单脉冲信号的模糊函数的matlab代码，可以方便的调用，已经验证(failed to translate)

文档，无线信道的matlab源程序，可以单独运行。 -word documents, Rayleigh fading channels Matlab source that can run.(word documents, Rayleigh fading channels Matlab source that can run.)

we can use this file for compressive sensing

Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重： 如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻起负面作用，则降低该特征的权重。(The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules: If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.)

一个关于matlab的基础知识的介绍，希望能对初学者有帮助！(A basic knowledge of matlab introduction, hoping to be helpful for beginners!)