opimize-code

说明：  一种基于概率的数据降维处理方法：Stochastic Neighbor Embedding(Based on the probability of data dimensionality reduction approach: Stochastic Neighbor Embedding)

打靶法求微分方程边值问题，这是数学上的求取方程问题的边值的方法 (Shooting method for boundary value problems for differential equations, which is to strike a mathematical equation of the boundary value problem approach)

导线网平差程序，参数约束，通过设定不同的PX达到经典自由网，普通自由网，拟稳平差效果，算例(Wire net adjustment procedures, parameters, constraints, and examples)

说明：  利用四阶龙格库塔求解微分方程，并给出方程实例。(The fourth order Runge Kutta is used to solve the differential equation and an example is given.)

说明：  用DFT 函数计算电压u, 电流i的基波(f1=50 Hz)的有效值和相位; 用FFT函数分别计算电压u和电流i 所包含的直流,基波和谐波的有效值和初相角; 可计算基波(f1=50 Hz)和各次谐波的功率p和功率因数con?.(The effective value and phase of fundamental wave (f1 = 50 Hz) of voltage U and current I are calculated by DFT function. The effective values and initial phase angles of DC, fundamental and harmonic waves contained in voltage U and current I are calculated by FFT function, respectively. The power P and power factor con of fundamental wave (f1 = 50 Hz) and harmonics can be calculated.)

用栈的思想实现的简易计算器，可直接输入表达式，然后自动计算结果(Ideology with a stack of simple calculator, you can directly enter an expression, then automatically calculated)

支持向量机和BP神经网络都可以用来做非线性回归拟合，但它们的原理是不相同的，支持向量机基于结构风险最小化理论，普遍认为其泛化能力要比神经网络的强。大量仿真证实，支持向量机的泛化能力强于BP网络，而且能避免神经网络的固有缺陷——训练结果不稳定。本源码可以用于线性回归、非线性回归、非线性函数拟合、数据建模、预测、分类等多种应用场合(Support vector machines and BP neural network can be used for non-linear regression fit, but they is not the same principle, support vector machine based on structural risk minimization theory, generally considered its generalization ability than the neural network of strong . Inherent defect- a large number of simulation confirmed that generalization ability of support vector machine is stronger than the BP network, but also to avoid neural network training results unstable. The source code can be used for linear regression, nonlinear regression, nonlinear function fitting a variety of applications, data modeling, forecasting, classification)

TGM.m \传统的Galerkin方法 MD.m \时滞惯性流形方法 brownian.m \演示布朗运动 randomwalk.m \ 演示随机游走 tumor.m \ 演示tumor演化(TGM.m traditional Galerkin method MD.m Delays inertial manifold method brownian.m demo Brownian motion randomwalk.m demo random walk tumor.m demo tumor evolution)

迭代学习控制算法的matlab程序，单输入单输出的。(Iterative learning control algorithm matlab procedures, single-input single-output.)

地球固连坐标系与地球惯性坐标系的转换矩阵程序，考虑的章动、岁差、自转等。(Earth' s solid even coordinate system with the Earth inertial coordinate system transformation matrix program, consider the nutation, precession, rotation, etc..)