FracLab-Mat

离散灰色的预测程序，利用最小二乘法预测数据(Discrete gray forecasting process, using least squares projections)

说明：  小生境遗传算法工具箱 很不容易才搜索到的 和大家分享啊 希望对大家有用哦(Niching genetic algorithm toolbox is not easy to search and hope to share useful ah oh)

生成进制数为4，调制指数为1的4CPFSK信号(Generate a hexadecimal number is 4, the modulation index for 1 4CPFSK signal)

simulink仿真实现DCDC升降压变换。内涵编号的文件以及参考文献进行参数设置(simulink Simulation DCDC step-down conversion. Connotation numbered files and references set parameters)

说明：  基于TOA定位算法的克劳美罗CRLB仿真程序(CRLB simulation program of TOA location algorithm)

基于Retinex理论的图像增强算法 及SSR 等算法 在低照度图像处理上有一定的效果(Image enhancement algorithm based on Retinex theory and SSR algorithm There is a certain effect in low illumination image processing.)

CSAAP lab2 bomblab自己做得(CSAAP lab2 bomblab)

小区初搜为GSM系统中的一个关键过程，本程序为GSM小区初搜过程的第二部，查找同步突发sch并定时的matlab程序，输入数据由采样数据得到，在转换成所需格式后进行处理。若其中包含sch,则输出找到信息，并计算得到定时信息。若没有，则查找下一个突发。内付算法详细说明文档(Area early in the search for the GSM system, a key process, the procedures for the GSM cell the second part of the beginning of search process to find the synchronous burst sch and timing matlab procedures, input data from the sampling data in converted into the required format for processing. If one includes sch, then output to find information and to calculate timing information. If not, then find the next emergency. Pay the algorithm in detail within the document)

说明：  关于大型机的内容，是cobol语言，大家可以仔细研习(Content on the mainframe is the cobol language, we can carefully study)

We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.