Time-series-analysis-CC-algorithm

一个用于解决马尔可夫过程的源代码,很适合学习随机过程的同学1(a Markov process for the settlement of the source code, are very suitable for studying stochastic process a classmate)

有限元方法fortran编程，包括二维三维线性非线性静态分析、稳定流瞬时流分析、振动问题、特征值问题、并行计算等。包含了所有子程序。(Finite element method fortran programming, including 2D and 3D linear and nonlinear static analysis, steady flow transient flow analysis, vibration problems, eigenvalue problems, parallel computing. Contains all subroutines.)

程序算任意点FFT和小波变换,以及可选择多种小波及小波变换后的单频带重够,另算信号的Lipschitz指数,高级数字信号处理!(counting procedures arbitrary point FFT and Wavelet Transform, and the choice of multiple wavelet and the wavelet transform of a single-band heavy enough, and another count signal Lipschitz index advanced digital signal processing!)

1、 写出此两点边值问题的积分形式； 2、 构造有限元方程； 3、 编程计算显示计算结果。(1, write the two-point boundary value of the integral form 2, structural finite element equation 3, programming calculations show the results.)

使用正交多项式完成数据拟合。程序对读入的gps采样点完成曲线拟合。()

关于房屋贷款贷款的计算，包含本息、本金、一次性付款等贷款方式(Calculated on mortgage loans, including principal and interest, principal, and other one-time payment of loans)

一个案例代码，用最小二乘支持向量机的，预测煤炭量(A case code, using the least squares support vector machine to predict the volume of coal)

FFT变换，有硬件说明架构和框图，说明傅里叶变换的原理和意义，同时附有128点的傅里叶变换(FFT )

cressman格点插到格点程序，从一个场插值出另一个分辨率不同的场(interpolates fields to another grid as specified )

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(Conjugate gradient method (Conjugate Gradient) is between the steepest descent method and Newton' s method between a method that takes only a first derivative information, but to overcome the slow convergence of the steepest descent method shortcomings, but also avoid the need to store Newton and computing the inverse Hesse matrix and disadvantages, conjugate gradient method is not only to solve large linear equations of the most useful methods, large-scale nonlinear optimization solution is the most efficient algorithms)