filter.conv

The goal of SPID is to provide the user with tools capable to simulate, preprocess, process and classify in vivo and ex vivo MRS signals. These tools are embedded in a matlab graphical user interface (GUI). (Pre)processing and classification methods can also be automatically run in a row using the matlab command line

说明：  matlab最优控制的作业 请各位高手多多指教(Matlab optimal control operations please master exhibitions)

用于基于图像纹理特征提取的图像检索，其中包括matlab中自带的graycomatrix和graycoprops两个m文件，和四个用于提取图像纹理特征及图像检索的m文件(For image retrieval, including matlab comes graycomatrix, and graycoprops two m files, and four m-files used to extract image texture features and image retrieval based on image texture features extracted)

说明：  几个关于matlab数值分析的源程序，跟大家交流学习一下！(Several numerical analysis on the matlab source, learn about the exchange with you!)

STBC MIMO 通信的代码，模拟了不同SNR下的BER。代码中，有注释说明(STBC MIMO communication code to simulate the BER in the SNR. Code, there are explanatory notes)

此代码将leach和deec协议进行比较，对毕设要坐这方面的同学很有帮助，大家有兴趣可以看看。(This code will leach and deec protocol comparison, the complete set up to take the students very helpful in this regard, we are interested can look at.)

传算法（Genetic Algorithm）是一类借鉴生物界的进化规律（适者生存，优胜劣汰遗传机制）演化而来的随机化搜索方法。它是由美国的J.Holland教授1975年首先提出，其主要特点是直接对结构对象进行操作，不存在求导和函数连续性的限定；具有内在的隐并行性和更好的全局寻优能力；采用概率化的寻优方法，能自动获取和指导优化的搜索空间，自适应地调整搜索方向，不需要确定的规则。遗传算法的这些性质，已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。它是现代有关智能计算中的关键技术(Propagation algorithm (Genetic Algorithm) is a law of evolution in biology class reference (survival of the fittest, survival of the fittest genetic mechanisms) randomized search method evolved. It was first proposed by the United States J.Holland professor in 1975, and its main feature is to operate directly on the structure of the object, the continuity of the derivative and the function limitation does not exist with global implicit parallelism inherent and better optimization capability the use of probabilistic optimization method that can automatically obtain and guidance to optimize the search space adaptively adjust the search direction, the rule does not require determined. The nature of the genetic algorithm, has been widely used in combinatorial optimization, machine learning, signal processing fields, such as adaptive control and artificial life. It is about smart modern computing key technologies)

clear all I=imread( lena.bmp ) figure imshow(I) I2=imrotate(I,-4, bilinear ) 逆时针旋转4度 figure imshow(I2) I3=fliplr(I) 垂直镜像 figure imshow(I3) I4=imresize(I,0.5, bilinear ) 缩小为原图的1/2 figure imshow(I4) A=double(I) 转换为double类型 计算7个不变矩 [nc,nr]=size(A) [x,y]=meshgrid(1:nr,1:nc) 得到网格 x=x(:) y=y(:) A=A(:) m.m00=sum(A) if m.m00==0 m.m00=eps end m.m10=sum(x.*A) m.m01=sum(y.*A) 计算均值 xmean=m.m10/m.m00 ymean=m.m01/m.m00 计算中心矩(li9_23.rar cm.cm00=m.m00 cm.cm02=(sum((y-ymean).^2.*A))/(m.m00^2) cm.cm03=(sum((y-ymean).^3.*A))/(m.m00^2.5) cm.cm11=(sum((x-xmean).*(y-ymean).*A))/(m.m00^2) cm.cm12=(sum((x-xmean).*(y-ymean).^2.*A))/(m.m00^2.5) cm.cm20=(sum((x-xmean).^2.*A))/(m.m00^2) cm.cm21=(sum((x-xmean).^2.*(y-ymean).*A))/(m.m00^2.5) cm.cm30=(sum((x-xmean).^3.*A))/(m.m00^2.5) im(1)=cm.cm20+cm.cm02 im(2)=(cm.cm20-cm.cm02)^2+4*cm.cm11^2 im(3)=(cm.cm30-3*cm.cm12)^2+(3*cm.cm21-cm.cm03)^2 im(4)=(cm.cm30+cm.cm12)^2+(cm.cm21+cm.cm03)^2 im(5)=(cm.cm30-3*cm.cm12)*(cm.cm30+cm.cm12)... *((cm.cm30+cm.cm12)^2-3*(cm.cm21+cm.cm03)^2)... +(3*cm.cm21-cm.cm03)*(cm.cm21+cm.cm03)... +(3*(cm.cm30+cm.cm12)^2-(cm.cm21+cm.cm03)^2) im(6)=(cm.cm20-cm.cm02)*((cm.cm30+cm.cm12)^2-(cm.cm21+cm.cm03)^2)... +4*cm.cm11*(cm.cm30+cm.cm12)*(cm.cm21+cm.cm03) im(7)=(3*cm.cm21-cm.cm03)*(cm.cm30+cm.cm12)... *((cm.cm30+cm.cm12)^2-3*(cm.cm21+cm.cm03)^2)... +(3*cm.cm12-cm.cm30)*(cm.cm21+cm.cm03)... *()

相关向量机用于风电场功率预测和各种大数据分类问题，单变量输出(Relevance vector machine for a wind farm power prediction and a variety of large data classification problem, univariate output)

SVM简单算法，利用该算法可以实现简单的几类数据的分类问题，非常简便(SVM simple algorithm, using this algorithm can achieve a simple classification of data types, very simple)