IFFT

Chebyew filter & matlab lab workshop ppt by vibhor kumar bhardwaj

这是一自适应噪声消除的matlab程序 算法使用的是NLMS 里面含有截取的噪声 有仿真图(This is an adaptive noise cancellation matlab program NLMS algorithm is used which contains a simulation of the interception of the noise figure)

The purpose of this tutorial is to gain familiarity with MATLAB’s Image Processing Toolbox. This tutorial does not contain all of the functions available in MATLAB. It is very useful to go to HelpMATLAB Help in the MATLAB window if you have any questions not answered by this tutorial. Many of the examples in this tutorial are modified versions of MATLAB’s help examples. The help tool is especially useful in image processing applications, since there are numerous filter examples.

fasica 独立成分分析MATLAB程序(fastica independent component analysis)

to generate the white noise signal u(n) with uniform distribution and power p

噪声调频信号的误码率的仿真过程，采用matlab语言(Noise FM signal BER simulation using matlab language)

svd和nmf的对比，在时间和效果对比，各个算法的特点(svd VS nmf)

periodogram is used to calculate the periods between the signals..Its efficiency is high compared to other techniques

为sinudoidal模型的AIC阶估计.AIC信息准则即Akaike information criterion，是衡量统计模型拟合优良性的一种标准，又由于它为日本统计学家赤池弘次创立和发展的，因此又称赤池信息量准则。它建立在熵的概念基础上，可以权衡所估计模型的复杂度和此模型拟合数据的优良性。 在一般的情况下，AIC可以表示为： AIC=2k-2ln(L) 其中：k是参数的数量，L是似然函数。 假设条件是模型的误差服从独立正态分布。 让n为观察数，RSS为剩余平方和，那么AIC变为： AIC=2k+nln(RSS/n) 增加自由参数的数目提高了拟合的优良性，AIC鼓励数据拟合的优良性但是尽量避免出现过度拟合(Overfitting)的情况。所以优先考虑的模型应是AIC值最小的那一个。赤池信息准则的方法是寻找可以最好地解释数据但包含最少自由参数的模型。(AIC order estimation for sinudoidal model)

说明：  自适应控制算法的另一个Simulink模型，可运行，是无模型参考控制算法的一个应用实例，供共同学习和交流(Adaptive control algorithm to another Simulink model to run, there is no model reference control algorithm of an application example for the common learning and exchange)