龙格库塔

多自由度轴承静刚度计算,求解速度较快。但只是静态下，不考虑离心力的作用(static stiffness calucate of bearing)

基于互相关分析的时延估计算法；基于互相关分析的时延估计算法(cross-correlation analysis for time delay calculation)

通过具有随机结构参数的四分之一车辆模型研究了具有不确定性结构参数的车辆在受到来自道路的随 机激励作用下的振动响应问题。将簧上质量、簧下质量、悬挂阻尼、悬挂刚度以及轮胎刚度均认为是随机变量。将路面的不平整引起的对车辆的激励看作高斯随机过程并通过简单指数功率谱密度来建立力学模型。(By a quarter vehicle model with random parameters studied vehicle structure uncertain structural parameters of the vibration by the random excitation the road response under question. The sprung mass, unsprung mass, suspension damping, suspension stiffness and rigidity of the tire are considered to be random variables. The excitation caused by uneven road vehicle regarded as Gaussian random process and to create a mechanical model of a simple exponential power spectral density.)

改进的极限学习机算法，具有更好的预测性能和稳定性(Improved limit learning machine algorithm)

SpaRSA算法作为解决凸优化问题的重要方法，在压缩感知等领域具有重要应用，这篇文章是SpaRSA算法的原始文章，学习这篇文章就可以进行SpaRSA算法程序的编写了。(SpaRSA algorithm to solve convex optimization problems as an important method in the field of compressed sensing and other important applications, this article is SpaRSA algorithm original articles, learning this article can be carried SpaRSA algorithm procedures for the preparation of.)

计算离散傅里叶变换的一种快速算法，简称FFT。快速傅里叶变换是1965年由J.W.库利和T.W.图基提出的。采用这种算法能使计算机计算离散傅里叶变换所需要的乘法次数大为减少，特别是被变换的抽样点数N越多，FFT算法计算量的节省就越显著。(A computing discrete Fourier transform fast algorithm, referred to as FFT. Fast Fourier Transform in 1965 by the JW Cooley and TW Tuji Ti out. Using this algorithm enables a computer to calculate the number of multiplications needed for the discrete Fourier transform greatly reduced, especially sampling points N is transformed more and save FFT algorithm to calculate the amount of the more remarkable.)

AFD（自适应傅立叶变换）的matlab实现代码(the matlab code of AFD algorithm)

说明：  共轭梯度法求解线性方程组,主要采用FR共轭梯度法(solve liner solutions from CG)

四阶龙格库塔算法，用来求解二阶偏微分方程，在转子系统的动力学方程数值求解中普遍应用(Runge Kutta algorithm)

适用于ABAQUS的自定义材料子程序，适用于Johnson-Cook材料模型(Apply to custom material ABAQUS subroutine for Johnson-Cook material model)