shanchen

实现多项式样条利率期限结构参数求解，方面做国债研究人员借鉴(Polynomial spline interest rate term structure parameters for solving aspects of the bond researchers draw)

实现1到1000位的大数运算（包括加减乘除和浮点数运算），运行环境是vs2005(1-1000, large number operations (addition, subtraction and floating-point), the operating environment is vs2005)

说明：  一个机器学习的python文件，里面拥有各种机器学习方法，可以供大家参考(A Python file for machine learning, which has various machine learning methods, can be used for your reference.)

使用Matlab编程，对教材74页例3.3.1进行编程仿真。其中，正电压A的值、噪声方差值、每个码元周期内的采样点数N自行设定（可设置为可调的变量）。噪声值可使用Matlab中产生高斯随机数的函数来进行仿真。贝叶斯检测判决式中，先验概率P(H1)=P(H0)，判断错误的代价因子设为1，判断正确的代价因子设为0. 按照上述参数的设定进行仿真，实现对仿真数据的贝叶斯检测判决；循环生成仿真数据，并进行判决结果的统计，即记录判决正确的次数，估计正确判决的概率。(The use of Matlab programming, teaching materials 74 pages of 3.3.1 programming simulation. Among them, the value of positive voltage A, the variance of noise, the number of sampling points in each symbol cycle (N) can be set by itself (adjustable variable). Noise values can be simulated using the function of generating Gauss random numbers in Matlab. In the Bias detection decision, the prior probability P (H1) =P (H0), the factor of error judgment is set to 1, and the correct cost factor is set to 0. According to the simulation parameters and realize the judgment of Bayesian detection simulation data; generating cycle simulation data, statistics and decision, which records the correct number of judgment, the estimated probability of correct decision.)

用于弹塑性本构的切线刚度计算，基于塑性本构的增量理论编写(flow theory coupled with damage failure criteria of the program for the vumat ABAQUS program, functional simulation load to failure of the process of destruction)

流形学习程序，Isomap，LLE，LTSA，etc，非线性数据降维(manifold learning, Isomap, LLE, LTSA, etc, nonlinear data dimensionality reduction)

迭代最小二乘法,反演中应用极广泛，非常经典(Iterative least-squares method，An extremely wide range of inversion, very classic)

用Fortran编程求解简单的一元二次方程案例(Solving quadratic equation of one variable)

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)

lagrange插值,用于分数时延滤波器farrow结构系数求解(Lagrange interpolation for fractional delay filter Farrow structure coefficient solution)