国外分享的采用偏最小二乘法处理程序

Matlab编写的相位展开(相位解缠)，程序实现两种相位展开(相位解缠)的算法，一个是质量图导引路径积分相位展开算法，另一个是Goldstein的枝切法。(2D PHASE UNWRAPPING ALGORITHMS for the phase quality guided phase unwrapping method and Goldstein s branch cut phase unwrapping method)

LTE系统链路级仿真,内有使用说明和源码(LTE system link level simulation, with instructions and source code)

包含位置式PID算法、积分分离式PID，现代信号处理中谱估计在matlab中的使用，计算多重分形非趋势波动分析matlab程序,采用热核构造权重，ML法能够很好的估计信号的信噪比,关于非线性离散系统辨识。

数字图像在产生过程中经常会受到噪音污染。因此，对于数字图像应该对其进行去噪音处理。在传统的基于傅里叶变换的信号去噪音方法中，可以使得信号和噪音的频带重叠部分尽可能的小，这样就可以在频域通过时，不需改变滤波方法而将信号和噪音分隔开来。但是，如果信号和噪音的频域重合时，用该方法进行噪音处理的效果就比较差。(digital image in the selection process will be subject to regular noise pollution. Therefore, the digital image should be carried out to deal with the noise. Based on the traditional Fourier Transform method of signal to noise, can result in a signal and noise bands overlap small as possible, so it can be adopted in the frequency domain, the need to change methods of filtering the signal and noise to separate. However, if the signal and noise in the frequency domain coincidence, the method for dealing with the effects of noise on the relatively poor.)

说明：  关于语音信号端点检测的有用文献，主要介绍了关于端点检测的有关技术和方法(Endpoint detection of speech signals useful literature are introduced on the endpoint detection of the techniques and methods)

将meanshift算法思想融入harris角点检测算法中，通过设置门限终止迭代漂移，亚像素级别地进行角点检测。(The mean shift algorithm ideas into a corner detection algorithm, terminate the iteration drift, carried out by the sub-pixel level corner detection limit by setting the door.)

各种资源分配算法实现，这是第二能量熵的matlab代码，完整的基于HMM的语音识别系统，最大似然（ML）准则和最大后验概率（MAP）准则，用蒙特卡洛模拟的方法计算美式期权的价格以及基本描述,非归零型差分相位调制信号建模与仿真分析 。

说明：  电路模拟的例程 包括图形 仿真的说明 欢迎大家下载(circuit simulation routines including graphic simulation Note welcome you download)

PLS回归模型建立的程序，针对多输入和多输出的。希望此方法能对大家有帮助(PLS regression model program, multiple-input and multiple-output targeted. I hope this method can help everyone)

程序来源：《复杂网络上的演化博弈》，这是一个规则网络上的牧鹿博弈(The source of the program is evolutionary game on complex networks, which is a deer game in scale-free networks.)