Autocorrelation_function

一个货物管理系，用的是面向对象的开发方法，里面所有说明齐全，点击startup就可以运行，名为good的文件夹里面是源代码。(A cargo management system, using object-oriented development methodology, which all the notes complete, click the startup will be able to run, to be called good folder is inside the source code.)

3GPP LTE-Advanced中OFDM实现仿真结果以及画出波形，为大家更加了解OFDM提供帮助(3GPP LTE-Advanced in OFDM achieve simulation results and draw the waveform, as we learn more about OFDM help Please help Google Translate improve quality for your language here.)

该软件实现渐变信号的瞬时频率提取，该算法采用基于小波脊的提取方法(Instaneous frequency extraction)

牛顿-拉夫逊潮流计算算例，包括自动执行模块的编写(Newton- Raphson power flow calculation examples, including the preparation of self-executing module)

自定义风格的SegmentedControl，IOS编程学习源码，很好的参考资料。(A custom style SegmentedControl, learning IOS programming source code, a good reference.)

说明：  ：Mean—shift算法是一种非参数密度估计算法，可以实现快速的最优匹配，在目标的实时跟踪领域起着非常 重要的作用。为了有效的将Mean—shift算法应用到灰度图像中，采用了以方向直方图建立目标模型的策略，提出了在灰 度图像中以Mean—shift为核心的目标跟踪算法。实验结果表明，该算法具有不受光照条件影响的优点，在低对比度的情 况下仍能实现稳定、实时的跟踪目标。(: Mean-shift algorithm is a nonparametric density estimation algorithm, the optimal matching can be fast, real-time tracking fields in the target plays an important role. In order to effectively Mean-shift algorithm will be applied to the gray image, the histogram used to establish the direction of the strategy target model is proposed in the gray image to Mean-shift tracking algorithm as the core. Experimental results show that the algorithm has the advantage of not lighting conditions, in the case of low contrast can still achieve stability, real-time tracking of targets.)

不同算法对时间序列进行奇异谱分解的源程序代码，matlab2006a平台调试通过(different algorithms on time series singular spectral decomposition of the source code, matlab2006a through debugging platform)

说明：  产生相机模拟实验标定板，行数，列数以及间距有自己设定，例如（张正友标定板（9,11,25））.(Simulation produces the camera calibration board, the number of rows, columns and spacing of their own settings, such as (Zhang Zhengyou calibration plate (9,11,25)).)

使用1749年至1924年太阳黑子的经典序列来确定和估计具有观测误差的模型(specification and estimation of models with observation errors using W?lfer’s classic time series of total number of sunspots from 1749 to 1924)

本程序为被动时间反转镜的信道多途压缩的仿真程序(Passive Time Reversal Mirror)