powell

很好用的单导线平差，具有单线的计算能力 可以已知两点或者方位角开始计算(Very good adjustment with a single wire, with one-way computing power can be known to start two or azimuth)

说明：  这是LU分解法求线性方程组的资料，讲解了LU分解的原理及过程，非常实用(LU decomposition seeking linear equations to explain the principles and process of the LU decomposition, very practical)

面向对象的有限元程序设计 ——空间8结点等参元的分析计算(Object-oriented finite element program design- space 8 node isoparametric element analysis calculation)

数值分析，即计算方法课程中的龙贝格算法源代码。(Numerical analysis, calculation of the Romberg algorithm source code in the methods courses.)

我自己用c语言写的64点基4FFT算法，在visual c++ 6.0环境下编译通过。同matlab结果一致。(My own use C language to write the 64 based 4FFT algorithm, in visual c++ 6 compiler environment through. Results consistent with matlab.)

music高阶谱分析算法，IDW距离反比加权方法，BP神经网络用于函数拟合与模式识别。( music higher order spectral analysis algorithm, IDW inverse distance weighting method, BP neural network function fitting and pattern recognition.)

FFT快速傅里叶变换 采用基4 fft实现的c语言版(FFT Fast Fourier Transform implemented using the base 4 fft c language version)

用流体计算李指数的。是用excel中的vba做的小程序。(calculated the lyapunov exponent)

针对传统的算法如遗传算法、粒子群算法等在TSP问题上求解精确性和求解规模上都还有一定的不足，本文提出了一种基于动态规划思想的粒子群优化算法。该算法用动态规划的方法实现粒子间的信息交互和粒子的进化，并且将粒子群中的粒子按无标度信息指导网络拓扑图的方式进行连接。仿真结果表明该方法能有效地减小误差率，提高解的精确，同时还保持了较低的计算复杂度，具有良好的稳健性。(TSP problem solving for the traditional algorithms such as genetic algorithms, particle swarm optimization accuracy and solving the scale, there is a certain lack of a dynamic programming algorithm-based particle swarm optimization algorithm. The algorithm using dynamic programming method to achieve the evolution of information exchange between the particles and the particles, and particle swarm particle scale-free information guide network topology map to connect. The simulation results show that this method can effectively reduce the error rate and improve the solution precision, while maintaining a low computational complexity, good soundness.)

一个简单的网格生成程序，操作方便，易学，类似于easymesh！(A simple grid generation program, easy to operate, easy to learn, like easymesh!)