OFDM

自己编的一个matlab 程序，先对图像进行加噪声，然后进行滤波，再进行边缘检测(Made themselves a matlab program, the first increase the image noise, and then filter, then the edge detection)

设计主动悬架控制系统框图，使用matlab软件建立主动悬架模型，在simulink中进行仿真计算，给出垂直加速度图。(Block diagram of control system design for active suspension, semi-active suspension model established using MATLAB software, the simulation in Simulink, given the vertical acceleration diagram.)

实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))

Useful tool for rendering and outputting information rich images(This function can be used in place of IMAGE, IMAGESC and IMSHOW, but does so much more. It is fast and displays images as they should be- correct aspect ratio, integer magnification, no axes. In addition, it can return the image as an output variable- useful for saving to disk, texture mapping surfaces, and post-rendering manipulation such as overlaying/combining two or more images. All the MATLAB built-in colormaps are implemented, but without MATLAB s nasty discretization artifacts. Plus, there are many new colormaps which are helpful for viewing more complex data, such as optic flow, likelihoods over images, difference images, segmentations, stereo image pairs (as anaglyphs) and edge-maps with orientation. It also accepts user defined linear and non-linear colormaps.)

Project for Cal Poly Pomona ARO 401 course.

mimo—ofdm线性卷积，实现输入的800位宽的数据同两个序列的卷积(Mimo- ofdm linear convolution 800 bits wide input data with the convolution of two sequences )

运用LS与MMSE进行信道估计仿真，并对两者的MSE进行比较(channel estimation simulation by ls and mmse ， to compare their MSE)

mehod of interpolation by bilinear,bicubic method, local histrogram,root mean square error,image negative

说明：  关于短波通信中多径的Matlab仿真代码(On short-wave communications in multi-path simulation of Matlab code)

说明：  指纹图像分割~利用分开的局部均值及方向场方法(~ Use of fingerprint image segmentation and direction of separate local mean field method)