DStheory

基于干扰矩阵的重置和导向矢量估计的数字波束形成，程序经过优化，可运行，里面包含了一个矩阵求积分的子程序，可参考(Reset based on interference matrix and steering vector estimation of digital beamforming, the program has been optimized to run, which contains a matrix integral subroutines, refer to)

说明：  模拟退火算法，地球物理反演，非线性反演算法(Simulated annealing algorithm)

内点法求解线性规划问题； 通过内点法实现了线性规划问题的求解； 内有说明文件；(Interior point method for solving linear programming problems through the realization of the interior point method for solving linear programming problem there is documentation )

常微分方程数值解法，又是一个数值分析的常用算法(Numerical Solution of ordinary differential equations, numerical analysis is a common algorithm)

python编写SM3密码杂凑算法,测试字符串abc, abcd*16(written in python SM3 password hash algorithm, the test string abc, abcd.* 16)

用Python语言写的多目标进化算法库（2017年最新版本），包含常见的多目标进化算法以及当前最新文献中的最新算法，能够实现不同算法之间的性能比较（包含常见的GD, IGD, HV等评价指标自动生成）。可以供进化计算、多目标优化、单目标优化算法的学习参考。Python语言版本简单易懂，实用性强。(Library of multi-objective evolutionary algorithm written in Python language (the latest version in 2017), including multi-objective evolutionary algorithm and the most common new literature in the new algorithm, can realize the performance between different methods (including the common GD, IGD, HV and other evaluation index generation). It can be used as a reference for evolutionary computation, multi-objective optimization and single objective optimization. Python language version is simple and easy to understand, practical.)

毕业设计有用，相控阵天线的方向图（切比雪夫加权），基于matlab GUI界面设计。( Graduation useful Phased array antenna pattern (Chebyshev weights), Based on matlab GUI interface design.)

用matlab所编用传输矩阵法计算光子晶体的能带结构的程序(prepared by using Matlab using the transfer matrix method photonic crystals with the structure of procedures)

经典99行拓扑优化程序，采用Heaviside方程获得接近0-1离散解(The classical 99-line topology optimization program uses Heaviside equation to obtain nearly 0-1 discrete solution)

用切比雪夫多项式逼近已知函数 用勒让德多项式逼近已知函数 用帕德形式的有理分式逼近已知函数 用列梅兹算法确定函数的最佳一致逼近多项式 求已知函数的最佳平方逼近多项式 用傅立叶级数逼近已知的连续周期函数 离散周期数据点的傅立叶逼近 用自适应分段线性法逼近已知函数 用自适应样条逼近（第一类）已知函数 离散试验数据点的多项式曲线拟合 离散试验数据点的线性最小二乘拟合 离散试验数据点的正交多项式最小二乘拟合 (By using Chebyshev polynomial approximation of the known functionApproximation of the known functions by Legendre polynomialsApproximation by rational fraction of known function in the form of PadmaTo determine the best uniform function polynomial approximation with the Lemez algorithmThe best known polynomial square for function approximationContinuous periodic function with Fourier series approximation of the knownApproximation of discrete data points in the Fu Liye cycleApproximation of the known function with adaptive piecewise linear methodAdaptive spline approximation ( first class ) known functionPolynomial curve fitting of discrete data pointsLinear least squares fitting of discrete data pointsOrthogonal polynomial least squares fitting of discrete data points)