warshall

This .m file is un simulation of a quantization of sine signal

matlab中求解一维非线性方程中孤子的演化(matlab for solving the sub-one-dimensional nonlinear evolution side Cheng Zhonggu)

计算诺特方程求解平面纵波入射到水平界面时的纵波反射系数与转换波反射系数 matlab图形化界面，输入上下两层介质的纵横波速度与密度即可，使用方便(Knott equations to calculate longitudinal wave reflection coefficients and converted wave reflection coefficient matlab graphical interface, enter the upper and lower layers medium density and shear wave velocity and longitudinal wave incident on a plane at the level of the interface can be easy to use)

simulated annealing 退货模拟算法实现(simulated annealing )

可以求取一维信号的模糊熵,比如心电信号就可以用这个程序来做模糊熵；另外一个是得出混淆矩阵(The fuzzy entropy of one dimensional signal can be obtained.For example, ECG signal can be used to do fuzzy entropy with this program.The other is to get the obfuscation matrix)

The optimization behavior of the self-adaptation (SA) evolution strategy (ES) with intermediate multirecombination (the (=I )-SA-ES) using isotropic mutations is investigated on the general elliptic objective function. An asymptotically exact quadratic progress rate formula is derived. This is used to model the dynamical ES system by a set of difference equations. The solutions of this system are used to analytically calculate the optimal learning parameter  . The theoretical results are compared and validated by comparison with real (=I )-SA-ES runs on typical elliptic test model cases. The theoretical results clearly indicate that using a model-independent learning parameter  leads to suboptimal performance of the (=I )-SA-ES on objective functions with changing local condition numbers as often encountered in practical problems with complex fitness landscapes.

BT法仿真，DFT变换，窗函数，功率谱，将加窗之后进行了补零(signal process)

给一段1s声音，添加入噪声，输出，然后去除噪声，输出(add noise to a 1s-length voice,excute it ,and remove the noise,and excute it)

这是TVAL3算法，是基于增广拉格朗日法和交替方向法的全变分最小化算法。这个算法是有关压缩感知的重建算法的例子。TVAL3算法是在最小全变分法的基础上，结合了增强型拉格朗日函数和交替最小化方法。通过交替最小化方法寻找增强型拉格朗日模型的最小值，再由最速下降法进行迭代，更新拉格朗日乘子。 (TVAL3: TV minimization by Augmented Lagrangian and ALternating direction ALgorithms.This algorithm is an example of a reconstruction algorithm for compressed sensing. The TVAL3 algorithm is based on the minimum total variation method, which combines the enhanced Lagrange function and the alternating minimization method. The minimum value of the enhanced Lagrange model is sought by the alternate minimization method, and then the iterative method is updated by the steepest descent method.)

根据已知数据拟合多次函数，自行修改数据和次数自动生成拟合函数(According to known data fitting multiple functions modify the number of automatically generated data and fitting function)