performance

K-mean方法聚类 实现多幅图像的K均值方法的聚类并显示(K-mean clustering，Efficient method to achieve multiple images of the K-means clustering method and display)

With this Matlab code one can can perform analysis of formants

说明：  matlab源程序的学习案例，方便大家学习，欢迎下载！！(matlab source case study, to facilitate learning, welcome to download! !)

solves a modified nonlinear Schr¨odinger Equation using the symmetric split-step method.

说明：  人工势场法避障 实现从势能高出往低处运动 ，实现路径规划 和避障(artificial potential)

contrast enhancement using sigma membership function and fuzzy method

zernike矩算法，matlab语言开发，可用于图像匹配等(zernike moments algorithm, Matlab language can be used for image matching, etc.)

matlab code generates egarchmodel

首先根据短训练字的特性进行相关运算，进行信号到达检测，当检测到相关值大于门限一定次数后，认为有信号到达。然后根据长训练字的特性，进行相关运算，进行OFDM符号FFT窗口起始位置的估计。估计出FFT窗口的位置后，先在时域进行小频偏的估计，将两个长训练字进行小频偏补偿后，进行FFT运算，根据FFT运算的结果进行整数倍频偏的估计。这些参数估计完成后，就可以进行数据解调了。先对数据部分进行完整的频偏补偿，然后根据估计的FFT窗口位置进行FFT运算得到频域的数据，进行解调。然后在对应于导频的子载波位置上提取出导频信息，根据导频信息估计出剩余定时误差以及剩余的信道响应误差，将误差量送入环路进行跟踪。当收到所有数据后，重新回到信号到达检测状态，进行下一次信号到达的检测和信号接收。(First, according to the characteristics of the short training word correlation operation, the signal reaching the detector, when the detected correlation value is greater than the threshold after a certain number of times that a signal arrives. And then the characteristics of long training word, the correlation operation for the FFT window starting position of an OFDM symbol estimate. The estimated position of the FFT window, the first small frequency offset in the time domain estimation, the two long training word small frequency offset compensation, the FFT operation, the FFT result of the operation for integer frequency offset estimate. These parameter estimation is completed, the data can be demodulated on. The first portion of the data for a complete frequency offset compensation, and based on the estimated FFT window position of the FFT operation to obtain frequency domain data, demodulated. Then corresponding to the position of the pilot subcarriers are extracted on pilot inform)

matlab工具箱 图像的处理 强大 可以看看 函数多(matlab image processing toolbox function can look more powerful)