ABL_Dataset_MatlabHelpers

matlab programme coading for load flow analysis in power system guass sidel newton raphson fast decoupled

Simulation BER of MQAM with M = 4 or 16 over fading and Rayleigh environment.

Mathworks公司文件交换不允许的。exe或。dll文件在提交包括在内。但有时一提交要求编制外部库。这次提交允许通过一个无缝的zip文件下载和安装的文件禁止通过谷歌网站托管。 默认情况下它会打开一个2MB的压缩文件，其中包含一个文件IDTF变成U3D文件（PDF格式制作的三维网格数字有用）转换器。 语法： installGoogleArchive（downloadLocation，zip文件）(The Mathworks File Exchange does not allow .exe or .dll files to be included in submissions. But sometimes a submission requires compiled external libraries. This submission enables seamless downloading and installation of forbidden files through a zip file hosted through Google Sites. By default it will unpack a 2MB zip file containing a converter for turning IDTF files into U3D files (useful for making 3D pdf figures from meshes). Syntax: installGoogleArchive(downloadLocation, zipFile))

PCM clustering algorithm

均匀圆阵的波束扫描代码，可以任意设置阵元个数和半径(Uniform circular array beam scan code, can be set arbitrarily array element number and radius)

分布式对MATLAB中图像处理的过程及相关函数进行详细讲解，帮助学生了解处理流程，熟练掌握函数使用。(Distributed process of MATLAB in image processing and related function in detail, help students to understand the process, familiar with function to use.)

This is a version of Foschini-Miljanic, an itarative algoriyhm for power control in wireless computer networks.

View dicom Picture use C++

以MATLAB將影像做邊緣偵測以及邊緣強化， 邊緣偵測分別為Prewitt以及Canny， 邊緣強化是將邊緣做銳利化(MATLAB will do to the image edge detection and edge enhancement, edge detection, respectively Prewitt and Canny, edge enhancement is done to sharpen the edge)

说明：  基于密度的聚类算法因其抗噪声能力强和能发现任意形状的簇等优点，在聚类分析中被广泛采用，本文提出 的基于相对密度的聚类算法，在继承上述优点的基础上。有效地解决了基于密度的聚类结果对参数值过于敏感、参数 值难以设置以厦高密度簇完全被相连的低密度簇所包含等问题。(Density-based clustering algorithm because of its strong resistance to noise and can find clusters of arbitrary shape, etc., in the cluster analysis is widely used, the proposed clustering algorithm based on the relative density, in succession on the basis of the above-mentioned advantages. Effectively solve the density-based clustering results on the parameter value is too sensitive, difficult to set the parameter value to high-density clusters of buildings connected to the low-density clusters are completely contained and other issues.)