基于Mean-shift的图像分割

电机转子台，断条缩孔的计算等，MATLAB等(Rotor sets, Breaking Shrinkage calculation, MATLAB, etc.)

粒子滤波的程序，经过调试的 能够正常使用，个人感觉还不错。(Particle filter procedures, after debugging. To normal use, personal feeling pretty good.)

这是一个经典的粒子滤波程序，供初学者学习。(This is a classical particle filter program, for beginners to learn.)

The following Matlab project contains the source code and Matlab examples used for continuous morlet wavelet transform. For documentation please refer to: http://arxiv.org/abs/0706.0099

K近邻算法在Matlab中的实现，相当完整，对研究KNN算法有一定帮助(K nearest neighbor in the Matlab, implementation, rather complete, the study of KNN algorithm has certainly helped)

基于matlab编程的经典Music算法，测量阵列信号波达方向。基于均匀线阵编程(DOA Music)

数据频域分解法，可能不是很全面，可以利用的这个方法的代码很少，本人也是从网上找的，可能不好理解，大家看看参考把(Data in the frequency domain decomposition method, may not be very comprehensive, code can use this method rarely, I also find from the Internet, you may not understand, we look at the reference to)

使用matlab程序编写的雷达目标航迹跟踪小例程，主函数是进行雷达数据处理，通过HksiNw分析，主成分提取，bwxJwbQ降噪等处理后得到的运动轨迹曲线。 (Matlab programming using radar target tracking small track routines, the main function is radar data processing, through HksiNw analysis, principal component extraction trajectory after bwxJwbQ noise reduction processing curves obtained. )

说明：  最小均方误差（LMS）自适应滤波器的matlab函数 lms.m(matlab function lms.m : LMS adaptive filter)

实现以下功能：装载信号；完成信号的单尺度一维离散小波分解；从系数中重构低频部分和高频部分；显示高频和低频部分；由小波逆变换恢复信号；多层一维分解；提取系数的低频和高频部分；重构第3层的低频系数；重构第1、2、3、4、5层的高频信号；重构原始信号并显示(Achieve the following functions: load signal complete signal single-scale one-dimensional discrete wavelet decomposition reconstructed from the coefficients in the low frequency and high frequency display high-frequency and low frequency restored by the inverse wavelet transform signal multi-layer one-dimensional decomposition extraction coefficient of low frequency and high frequency reconstruction of 3-layer low-frequency coefficients reconstruction of the first layer of high-frequency signal 1,2,3,4,5 reconstruct the original signal and display)