ofdm_without_noise

说明：  苏金明《Matlab图形图像》。 本书主要介绍了MATLAB图形图像的基础——句柄图形对象，以及图形着色、光照、材质、纹理映射、透明性和交互操作等高级绘图技术，然后介绍图像处理、虚拟现实和地图制作等几个图形图像方面的工具箱内容全面,可供对有关内容感兴趣的大学生 研究生和科研技术人员参考。(matlab picturing)

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)

对预处理及分割之后的图像进行识别 利用BP神经网络进行训练 学习(On after pretreatment and segmentation of image recognition using BP neural network for training study)

用matlab编程工具，编写具有操作界面的应用程序，通过菜单、对话框，选项框等界面控制，对算法进行演示。需要在应用系统中实现的算法及功能包括： 1、图像增强算法 （1）灰度线形变换：亮度及对比度可以调节（通过控制参数的改变，能够实时预览变化结果）； （2）直方图均衡：可在界面上对比均衡前后的效果。 2、图像变换算法 （3）对一幅彩色图像进行DCT变换和反变换，对比结果和原图； （4）仅保留左上角16X16的DCT系数，进行反变换，计算结果图的信噪比SNR。 3、图像分割算法 （5）采用最优阈值算法对灰度图像进行分割； （6）用Canny算法对灰度图像进行边缘检测； （7）用hough变换，检测边缘图像中的直线，并用不同颜色将检测出的直线叠加显示到原图像上。 (Preparation of a user interface with Matlab programming tools, applications, menus, dialog boxes, option boxes and other interface control, the algorithm demo. Algorithms and functions that need to be achieved in the application system including: 1, the image enhancement algorithm (1) gray linear transformation: the brightness and contrast can be adjusted (by controlling the change of the parameters, it is possible to real-time preview changes result) (2) Histogram equalization : contrast before and after equalization effect in the interface. 2, an image transformation algorithm (3) for a color image DCT transform and inverse transform, comparing the results and the original (4) to retain only the upper left corner of 16x16 DCT coefficient, the inverse transform, the signal-to-noise ratio SNR calculation results of FIG. . 3, image segmentation algorithm (5) The optimal threshold algorithm to gray-scale image segmentation (6) Canny algorithm for edge detection of gray-scale images ()

测量粗差中抗差滤波算法加权函数的对比，程序能够运行，函数对比结果画图呈现。(weighting function comparison in robust filter.)

说明：  多目标规划的概念是 1961年由美国数学家查尔斯和库柏首先提出的。多目标最优化思想，最早是在1896年由法国经济学家V.帕雷托提出来的。他从政治经济学的角度考虑把本质上是不可比较的许多目标化成单个目标的最优化问题(The concept of multiobjective programming was first proposed by Charles and Cooper, American mathematicians, in 1961. The idea of multi-objective optimization was first put forward by the French economist v. Pareto in 1896. From the perspective of political economy, he turned many objectives that are essentially incomparable into optimization problems of a single objective)

clustering algorithms in matlab

基于开源资料开发的大整数简单运算的函数库(big-number library for encryption development)

Mathematic model of acoustic field for ultrasonic transducers according to "Ultrasonic beam structures in fluid media" paper

一个小的lindo，做数学建模的同志们应该知道吧，不知道你们用得上不。以后有好东西再给大家送来(A small lindo, make mathematical modeling comrades should know, I do not know you is not useful. After the U.S. has brought good things to give)