MESH-FREE-MLS-SHAPE-FUNCTION

计算一般的mie散射光强等参数的精确程序，得到muller矩阵的各个元素表达式(scattering of Mie)

此代码属于地球物理领域，是用有限差分开发的直流电法三维正演，基于FORTRAN平台，此代码具有很高的运算效率，对于从事地球物理领域的人来说是不可多得的(This code belongs to the field of geophysics, is developed using finite difference method of three-dimensional forward modeling of DC, FORTRAN-based platform, this code has high computing efficiency, people engaged in geophysical field is rare)

用matlab实现新的启发式算法—蝙蝠算法，用于生产优化问题(New heuristic- bat algorithm for the production optimization problem using matlab )

说明：  基于神经网络的数字预失真技术，即智能DPD(Digital Predistortion Technology Based on Neural Network)

说明：  共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method Gradient) is a method between the steepest descent method and Newton's method. It only uses the first derivative information, but overcomes the disadvantage of slow convergence of steepest descent method, and avoids the disadvantage of storing and calculating Hesse matrix and solving inverse of Newton's method. Conjugate gradient method is not only one of the most useful methods to solve large-scale linear equations, but also the most effective method to solve large-scale nonlinear optimization One of the algorithms of. Among all kinds of optimization algorithms, conjugate gradient method is very important. It has the advantages of small storage, step convergence, high stability and no external parameters.)

说明：  此是多峰函数MATLAB程序，多峰函数在解决多峰曲线问题中经常会用到，有此程序代码可以省去很多麻烦。(This is a multi-peak function MATLAB program, multi-peak function, multi-peak curve in the settlement of the question is often used, there is such a code can save a lot of trouble.)

根据当前运动模型，进行Kalman滤波。得到滤波优化后的运动轨迹(Kalman filtering is carried out according to the current motion model)

Training a 3 layers feed forward neural network using back propagation algorithm

c/C++跟fortran语言之间的一些转换(c/C fortran language with the conversion between)

利用MATLAB实现了16位快速傅立叶变换，并与自包含函数进行了比较。(The 16-bit Fast Fourier Transform is realized by using MATLAB and compared with the self-contained function.)