kftry

将感兴趣的边缘覆盖到原图上，显示分割的效果，很有帮助哦(Will be of interest to the artwork on the edge of coverage, showing the effect of segmentation, helpful oh)

一个matlab实现bp的源文件，也许各位用得上，请大家多多指教(Bp realize a matlab source files, perhaps you useful, please everyone exhibitions)

简单介绍脉冲压缩前后的对比，数据清晰明了，代码简单易懂，使读者能够直观读懂脉冲压缩体制(Compare before and after a brief pulse compression, data clarity, the code is simple to understand, so that readers can intuitively understand the pulse compression system)

稀疏表达人脸识别算法相关例程,并附带l1magic PDF文档(src face recognition)

说明：  该函数提供了一种时变维纳滤波器的实现。这种维纳滤波器可以处理非平稳信号。 在给定噪声信号和参考信号的情况下，Wiener滤波器可以应用于噪声信号以估计与参考信号相干的贡献。(This function provides an implementation of a time-varying Wiener filter. This kind of Wiener filter can deal with non-stationary signals. Given a noisy signal and a reference signal, the Wiener filter can be applied to the noisy signal for estimating the contribution coherent with the reference signal.)

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.

说明：  本程序实现的功能是：bpsk在matlab上的调制解调(modulation and demodulation of bpsk on matlab.)

随机权重法改进粒子群优化算法， 更换目标函数后使用(Random weight method to improve particle swarm optimization algorithm, the objective function after the use of replacement)

对比了基于二阶和高阶统计量的DOA 估计算法性能，仿真结果表明，基于高阶统计量的DOA 估计算法具有更好的性能(Compare the performance of DOA estimation algorithm based on second-order and higher-order statistics, simulation results show better performance DOA estimation algorithm based on higher order statistics)

用于解决0-1规划问题，采用比分支界定法更加迅速的方法(0-1 programming problem to solve, using the branch and bound method is more rapid than the method)