LMS_RLS

helpul code to finds the shortest path bounded

此文件为模拟zernike波面拟合图像与原始波面图形的误差的图像。通过模拟真实环境的随机误差，得到误差函数的波面(This file is simulated zernike Wavefront fitting the image with the original wave-front error of graphic images. By simulating the real environment, random error, the wavefront error function to be)

天线接收信号时，突然出现一个干扰信号，并且干扰信号从０°开始，绕９０°，观察ＳＩＮＲ的变化规律(Antenna signal, suddenly appeared a jamming signal, and the interference signal from the 0 ° starting around 90 °, observed variation of SINR)

针对HHT中存在的边界效应，提出了镜像拖延发改进EMD的分解过程。并提供了英文原版文献便于理解。适用于HHT研究的提高研究学习(improved HHT base on masking technology. in order to reduce the end effect in hilbert huang transform)

matlab下用dspbuilder编写的FM调制波形例子，比较初级，供新手学习。(Under matlab prepared dspbuilder FM modulation waveform example, compare the primary for the novice to learn.)

基于GABOR小波对ORL人脸库进行特征提取，程序简单，适合初学者(With GABOR wavelet feature extraction in ORL face database, procedure is simple to understand For beginners)

调用属性依赖度函数的程序。中间数据替换为自己要分析的数据即可。

独立成分分析（Independent Component Analysis, ICA）是近年来发展起来的一种有效的盲分离技术，最早是由法国学者Herault和Jutten于1986年提出。ICA方法的提出最初是用来解决“鸡尾酒会”问题，其过程可以归纳为，在源信号与传输通道参数均未知的情况下，仅根据源信号的统计特性，出现测信号恢复出源信号。ICA分析的关键在于根据一定的优化准则建立描述输出信号独立程度的优化判据，即目标函数，并设计相应的优化算法，寻求最优的分离矩阵，使得输出信号中各分量尽可能相互独立。采用ICA方法对信号进行盲分离时，可避免过多地受大能量噪声成分的影响，将部分小能量信号源识别出来。随着ICA技术的不断发展，目前ICA技术已经广泛应用于语音增强、音频识别、通信、医学信号处理、金融数据挖掘、图像消噪、数字水印、遥感等领域，并取得了一定的研究成果。(Independent Component Analysis (ICA) Component ini order, developed in recent years is a kind of effective separation technology, originally from French scholars Herault and Jutten in 1986. The proposed method is initially ICA to solve the "cocktail" problem, the process can be divided into, in the source signal transmission channels and in the case of unknown parameters according to the source of the signals, and the statistical characteristics of recovering the source signal. According to the analysis of the ICA key lies in the establishment of optimal criteria described the output signal of the independent, objective function optimization criterion, and the corresponding optimization algorithm, the optimum )

MATLAB simulation of group velocity dispersion in an optical fiber

说明：  地心地固（ECEF）坐标系下，基于广义最小二乘的雷达组网空间误差配准(Radar network based on generalized least square error of registration space)