基于灰度的图像匹配

用于盲信号分离的LMS算法，可以从混合的观测向量中分离出需要的信号，判读的标准是计算串音误差(For the LMS algorithm for blind signal separation can be observed from the hybrid vector needs to separate out the signals, the standard interpretation is to calculate the crosstalk error)

MPSK和QAM仿真，AWGN信道，误码率与Es/N0的关系和理论关系式的对比。(MPSK or MQAM modulated signal s relationship between BER and Es/N0 in AWGN channel,compared with the ideal function given by theory.)

本文针对SLAM数据关联中使用最为广泛的最近邻方法作了改进，利用特征估计位置与载体预测位置之间的欧氏距离计算代替了全部特征与每个量测之间的马氏距离计算，避免了大量的矩阵乘法计算。该算法简单易行，降低了算法的计算复杂度，有利于SLAM算法的实时执行，且关联效果与全局最近邻法相同(In this paper, SLAM data association in the most widely used methods of improving the nearest neighbor, using the characteristics of the estimated location and the location of vector prediction Euclidean distance between the calculation instead of all the characteristics of each measurement between the Mahalanobis distance calculation, to avoid a large number of matrix multiplication calculation. The algorithm is simple, the algorithm to reduce computational complexity and is conducive to the implementation of real-time SLAM algorithm, and the effects associated with the same overall nearest neighbor method)

实现非均匀傅里叶变换代码，可用于石油地震勘探、航空航天、图像处理，电子电工方向。(Achieve non-uniform Fourier Transform code, can be used for seismic exploration, aerospace, image processing, electronics and electric direction.)

用matlab产生m序列的程序,很好的程序,好不容易找到的,可以下载.(M sequences generated by matlab procedures, good procedures, hard to find, and can be downloaded.)

说明：  对一个随机信号进行包络检波，并且实现包络检波，分析误码率随信噪比变化的趋势，画出波形。(Signal spectrum modulation)

在大多数图像和信号处理，我们需要预处理工具，以提高他们的素质和有更好的结果。此类工具之一过滤在此文件中存在一些人。

说明：  matlab实现的语音分析，其中，有lpc分析。程序都经过软件验证，没有错误。(matlab implementation of speech analysis, of which there lpc analysis. Software programs have been validated without error.)

最优化计算一书中非最小二乘优化问题源代码，已通过测试，可直接运行！(Optimize the calculation of a book of non-least squares optimization problem source code has been tested and can be run directly!)

emprical model decomposition经验模态分解，可以对随机信号自动分解成本征模函数，matlab实现代码(emprical model decomposition)