Signal_Processing

matlab code for database creation

图像融合评价指标，包括有：均值，标准差，信息熵，平均梯度，相关系数，扭曲程度，偏差指数。每个指标都分别对RGB三个波段进行评价。(This file refers to the ution factor of image fusion,which including:mean,standard deviation,information entropy,average gradient,correlation cofficient,distortion and bias index.Each factor is used to ute every band of RGB of fusion results. )

这是一个matlab关于模型预测控制的例子，主要是一个机械转台的控制仿真，希望对学习模型预测控制的同学有帮助(This is an example matlab on model predictive control is mainly a mechanical turntable control simulation, in the hope of learning model predictive control to help students)

有限元PlaneTrussElement的matlab程序(FEA PlaneTrussElement)

说明：  　 随着微加工技术的发展和日益成熟 ,微型化光谱仪的研究得以快速发展。和传统的 微型光谱仪相比 ,基于调制原理的光谱仪具有高光通量、 高分辨率的性能优势 ,可广泛应用于生物、化学、 医学等许多领域中对微弱辐射信号的探测。介绍了几种类型的调制光谱仪的结构特点和关键技术 ,分析了设计与制作微型调制光谱仪过程中存在的一些关键问题与难点 ,并总结了该领域的研究进展和发展趋势。(　The mat uration of the optical micro2elect ro mechanical systems technology has imp ul sed t he development of t he micro spect rometer . Compared to the t raditional micro spect rometer , t he spect rometer based on modulation can be used in biological , chemical and medical fields to detect t he faint signal s due to it s inherent advantages. An overview of t he development s of t he micro spect rometer based on modulation is presented. The key p roblems in designing and fabricating t he Fourier t ransform spect rometer ( F TS) are discussed , and t he progresses made worldwide in t his field are al so presented.)

说明：  珍藏版，可实现，新K均值聚类算法，分为如下几个步骤： 一、初始化聚类中心 1、根据具体问题，凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。 2、用前C个样本作为初始聚类中心。 3、将全部样本随机地分成C类，计算每类的样本均值，将样本均值作为初始聚类中心。 二、初始聚类 1、按就近原则将样本归入各聚类中心所代表的类中。 2、取一样本，将其归入与其最近的聚类中心的那一类中，重新计算样本均值，更新聚类中心。然后取下一样本，重复操作，直至所有样本归入相应类中。 三、判断聚类是否合理 采用误差平方和准则函数判断聚类是否合理，不合理则修改分类。循环进行判断、修改直至达到算法终止条件。(NewK-means clustering algorithm ，Divided into the following several steps: A, initialize clustering center 1, according to the specific problems, from samples with experience selected C a more appropriate focus the sample as the initial clustering center. 2, with former C a sample as the initial clustering center. 3, will all samples randomly divided into C, calculate the sample mean, each the sample mean as the initial clustering center. Second, initial clustering 1, according to the sample into the nearest principle clustering center represents the class. 2, as this, take the its recent as clustering center of that category, recount the sample mean, update clustering center. And then taking off, as this, repeated operation until all samples into the corresponding class. Three, judge clustering is reasonable Adopt error squares principles function cluster analysis.after clustering whether reasonable, no reasonable criterion revisio)

一些常用的CFD差分格式的代码，新学的用起来挺好的(some basic code for cfd )

光伏pv特性图，在2010下可以直接仿真出波形(Photovoltaic pv diagram, can direct simulation waveform under 2010)

matlab时频分析工具箱(附安装方法和函数说明) 这是一个工具箱源码程序，需要对大家有用(time-frequency analysis matlab toolbox (with installation method and function description) This is a toolbox source program, you need to be useful to everyone)

Program for Space-Time-Block-Code BPSK modulation performance as a function of SNR and BER. (MATLAB)