搜索资源列表
ARMODEL
- 功率谱估计的应用范围很广,在各学科和应用领域中受到了极大的重视。在《现代信号处理》课程中讲述了经典谱估计和现代谱估计这两大类谱估计方法;经典谱估计是基于傅立叶变换的,虽然具有运算效率高的优点,但是频谱分辨率低同时旁瓣泄漏严重,对长序列有着良好的估计。为了克服经典谱估计的缺点,人们开展了对现代谱估计方法的研究。现代谱估计是以随机过程的参数模型为基础的,有最大似然估计法、最大熵法、AR模型法、预测滤波器法。现代谱估计对短序列的估计精度高,同经典谱估计互为补充。在认真学习了现 代谱估计方法后,我选择了
实验2-插值与拟合
- 1、掌握用MATLAB计算拉格朗日、分段线性、三次样条三种插值的方法,改变节点的数目,对三种插值结果进行初步分析。 2、掌握用MATLAB作线性最小二乘的方法。 3、通过实例学习如何用插值方法与拟合方法解决实际问题,注意二者的联系和区别。-1. Grasp by matlab calculating Lagrange, segement linear, 3rd order spline these 3 interpolation method. Analisize the 3 interpola
7879
- 这是matlab中的一个例子,请注意下载-This is the one example, attention is drawn to download
CrossPointNo
- CrossPointNo=53 %%%输入图中节点的总数目 对已知的边进行赋值,注意:有向图的Cost(i,j)=Cost(j,i)-CrossPointNo = 53%%% imported map nodes to the total number of known side Fu value, attention : to map Cost (i, j) = Cost (j, i)
yichuansufagongju
- 大家都需要的遗传算法工具,大家要下的快抓紧点下!-We need the tools of genetic algorithm, we must pay close attention to the point where fast!
jiandan0101
- 这是一个非常简单的遗传算法源代码,代码保证尽可能少,实际上也不必查错。对一特定的应用修正此代码,用户只需改变常数的定义并且定义“评价函数”即可。注意代码 的设计是求最大值,其中的目标函数只能取正值;且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用 Gaussian变异替换均匀变异,可能得到更好的效果。代码没有任何图形,甚至也没有屏幕输出,主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu, 目录 coe/evol中的文件prog.c中
Difds3
- 用LAPLACE方法求解多维沃尔泰拉方程,此处为一个变元的方程,由于该方程同时含有微分和积分,一般求解有一定的困难。此处为MATLAB程序,注意不同的边界条件-used method for multiple preoperational Ertaila equation here as a variable element of the equation, As the same time contain differential equations and integral, the gen
Saliency Toolbox2.2
- The SaliencyToolbox is a collection of Matlab functions and scr ipts for computing the saliency map for an image, for determining the extent of a proto-object, and for serially scanning the image with the focus of attention. It has been cited in more
PCA_LDA.rar
- 《机器学习》课上的作业,PCA和LDA降维,尽管网上很多,但很少注释,另外细节上也没注意。这里有很详细的注释。另外还附上一个Naive贝叶斯分类器,大家可以作比较。附带的图像包是OLR人脸。ReducedDim为想要提取的特征数,不是百分比!," Machine learning" classes on the homework, PCA and LDA dimensionality reduction, even though a lot of online, but f
cluster.rar
- 用matlab实现聚类算法,注意是层次聚类和未知类别聚类算法!,Clustering algorithm using matlab implementation, pay attention to are hierarchical clustering and unknown type of clustering algorithm!
SaliencyToolbox
- Koch等人最新的注意力选择算法matlab工具箱2006版-Toolbox code of Attention Selection model by Koch 2006
Saliency
- 利用视觉注意机制生成显著图(包括matlab程序、exe程序和相应的文章)-Use of visual attention mechanisms generate significant plan (including the matlab program, exe and the related article)
2
- 一种求邻接矩阵的普通算法,这是通用程序,要注意变量的更改。-A Method for the adjacency matrix of the general algorithm, which is common procedure, to pay attention to the variable changes.
WTB_v3
- 本程序为丹麦奥尔堡大学开发的基于Matlab/Simulink的风电专用工具箱,包含专用的风模型、电机模型、变换器及控制策略等内容,著名的风电软件DIGSILENT等软件就是基于该软件开发的。-This toolbox has been developed during the research project “Simulation Platform to model, optimize and design wind turbines” and it has been used as a g
itti-koch-1998
- 有关视觉注意机制的文章,英文原文,itti-Articles on visual attention mechanisms, the English original, itti
radon56
- 车牌水平矫正中radon变换的应用,注意radon变换检测直线方向有几种,有基于投影最大值的,有基于车牌字符空隙的等。-The level of radon transform plate correction application, pay attention to radon transform to detect straight line there are several, with the maximum value based on the projection, there a
txt
- 们讨论图像的重构。我编写的重构程序中,为了比较分解图像和重构图像,首先绘出经过小波分解的图像,然后再进行重构。在绘制分解图像和重构图像的过程中,要注意数据格式的转换。-Image Reconstruction discussed. I prepared reconfiguration process, in order to compare decomposition of images and reconstruction of images, first of all draw after
matlab_colormap
- 可以将图的颜色在0位置表现为白色,使用方法为multimap函数,注意将范围设为对称,这样就可以将0设为白色-Can map the location of the performance of the color 0 is white, the use of methods for Multimap function, set the scope of attention to symmetry, this can be 0 is set to white
matlab_study_experience
- matlab非常重要的几点经验,非常值得留意和注意。-matlab a few very important experience, very worthy of attention and attention.
matlab
- this ile has been written to my friends in pudn and i believe it is useful for u. tjhanks for ur attention -this ile has been written to my friends in pudn and i believe it is useful for u. tjhanks for ur attention
