33

这是一个自适应滤波的matlab源程序，已经通过调试，可以直接看图(This is an adaptive filtering matlab source, has been through the debugging, you can directly Figure)

mpu6050模块测试，mpu6050的测试程序，用于读取mpu6050的测试值，简单作为大家的参考资料(mpu6050 test procedures，mpu6050 test program for reading test values ​ ​ mpu6050 and simple as a reference for everyone )

线性化反馈的自适应模糊滑模控制 详细的程序和simulink图 希望对大家有帮助(the code of liner feedback and fuzzy sliding mode)

说明：  讲解数字PID很好的电子书，里面有现成的matlab源码，比较实用。(Digital PID on a good e-books, there are ready-made source matlab, more practical.)

若不希望用与估计输入信号矢量有关的相关矩阵来加快LMS算法的收敛速度，那么可用变步长方法来缩短其自适应收敛过程，其中一个主要的方法是归一化LMS算法（NLMS算法），变步长 的更新公式可写成 W（n+1）=w（n）+ e（n）x（n） =w（n）+ （3.1） 式中， = e（n）x（n）表示滤波权矢量迭代更新的调整量。为了达到快速收敛的目的，必须合适的选择变步长 的值，一个可能策略是尽可能多地减少瞬时平方误差，即用瞬时平方误差作为均方误差的MSE简单估计，这也是LMS算法的基本思想。 (Want to estimate if the input signal vector and the relevant matrix to speed up the convergence rate of LMS algorithm, then the variable step size method can be used to shorten its adaptive convergence process, one of the main method is normalized LMS algorithm (NLMS algorithm) , variable step-size update formula can be written W (n+ 1) = w (n)+ e (n) x (n) = w (n)+ (3.1) where, = e (n) x (n) the right to express filter update vector iterative adjust the volume. In order to achieve the purpose of fast convergence, we must choose the appropriate value of variable step size, a possible strategy is as much as possible to reduce the instantaneous squared error, which uses the instantaneous squared error as the mean square error MSE of the simple estimate, which is the basic LMS algorithm思想.)

说明：  本程序自己谢的卷积盲分离的程序，调用了几个函数！(This procedure Xie own Convolution Blind Separation of procedures, a few function calls!)

calculating fiber eigen modes (calculating fiber eigen modes)

定位指纹，室内，算法，欧式距离，最大后验概率，贝叶斯，加权贝叶斯，等(Location, fingerprint, interior, algorithm, Euclidean distance, maximum posterior probability, Bayes, weighted Bayes, etc.)

一种利用小波包变换进行盲信号分离的程序。(Program for blind source separation using wavelet packet transform.)

一个关于MATLAB的简单的曲线拟合GUI代码。(A simple curve fitting on MATLAB GUI code.)