nonlinear-optium

四犬相逐问题的计算机模拟 mathematica程序源代码 (Four dogs with the problem by computer simulation source code mathematica)

burgers方程求解，采用fortran编写，有详细的说明，效果非常好(burgers equations, using fortran prepared a detailed description of the effect is very good)

二维情况的chan定位算法，1994年原版论文代码实现，可以支持远近和linear nonlinear四种模式(2 dimension chan algorithm, TDOA localization. Including near, far field and linear nonlinear sensor array)

该程序用fortran90编写，时域有限差分（FDTD)中的近远场变换方法。解决了电磁波后向散射中的RCS计算(FORTRAN90 prepared with the program, finite difference time domain (FDTD) in the near field to far field transformation method. Resolved backscattering of electromagnetic waves in the RCS calculation)

有限体积法计算二维方腔流（含数值算法介绍及C++，Fortran源代码）(Calculation of two-dimensional cavity flow with finite volume method (including introduction of numerical algorithm and C++, Fortran source code))

说明：  c语言编写的高效用LU分解法求任意维数的矩阵的逆，它是经典书籍《算法导论》（第二版）中矩阵求逆的c语言实现。 (The algorithm of matrix inverse is based on LU decomposition which is proposed by the book of introduction to algorithm (second edition).)

支持向量机作为统计学习理论的实现方法，能很好地解决非线性和高维数问题，克服了神经网络方法收敛慢、解不稳定、推广性差的缺点，近年来得到了广泛地研究，在模式识别、信号处理、控制、通讯等方面得到了广泛地应用。(Support Vector Machine as the implementation of statistical learning theory approach, can be a good solution to the nonlinear and high dimension problem, the neural network method to overcome the slow convergence, solution instability, bad promotion of sexual shortcomings, in recent years has been widely studied, at pattern recognition, signal processing, control, communications, etc. has been widely applied.)

邻带计算，高斯正反算，可以实现测绘系统内简单的转换计算，但是是基于80坐标系统的。(failed to translate)

fortran 写的摩尔库伦本构模型，供写材料umat的人参考(fortran write the molar Coulomb constitutive model for people to write reference materials umat)

一维欧拉方程计算，集合了Lax-Friedrichs，Richtmyer，MacCormack，Steger-Warming，Van Leer，AUSM，Zha-Bilgen，Godunov，Osher，Roe，Rusanov，HLL(HLLE)，HLLL，AUFS方法(One dimensional Euler equation, including Lax-Friedrichs, Richtmyer, MacCormack, Steger-Warming, Van Leer, AUSM, Zha-Bilgen, Godunov, Osher, Ro, Rusanov, HLL(HLLE), HLLL, AUFS)