photonic_crystal_method_of_characteristic_matrix_1

说明：  《遗传算法及其在电力系统中的应用》华中科技大学版("Genetic Algorithms and Their Applications in Power Systems" 2002)

说明：  基于CORDIC算法计算反正切函数。输入横坐标纵坐标及迭代次数，输出角度及弧度值；附CORDIC英文文档说明(atan function based in CORDIC algorithm)

说明：  C语言编写8个点的FFT程序,在WINTC上编译通过(C language 8 point FFT procedures WINTC compiled through)

本书介绍了XFEm在结构件的断裂分析中的应用(this book introduces the application of XFEM in the field of fracture analysis)

高斯-赛德尔迭代法是解线性方程组的常规算法，本文是C语言的高斯-赛德尔计算代码(Gauss-Seidel C program)

说明：  levenberg-maquardt最小二乘拟合算法(This program do the levenberg-maquardt LS fit.)

迭代算法用在曲面，曲线拟合，很好的一个算法(The iterative algorithm used in the surface, curve fitting, a good algorithm)

mimo系统中在高信噪比下，一个发射天线，两个接收天线的性能仿真。(mimo systems at high signal to noise ratio, a transmitting antenna, two receive antenna performance simulation.)

3．1 线性方程组类设计 3．2 全选主元高斯消去法 3．3 全选主元高斯-约当消去法 3．4 复系数方程组的全选主元高斯消去法 3．5 复系数方程组的全选主元高斯-约当消去法 3．6 求解三对角线方程组的追赶法 3．7 一般带型方程组的求解 3．8 求解对称方程组的分解法 3．9 求解对称正定方程组的平方根法 3．10 求解大型稀疏方程组的全选主元高斯-约当消去法 3．11 求解托伯利兹方程组的列文逊方法 3．12 高斯-赛德尔迭代法 3．13 求解对称正定方程组的共轭梯度法 3．14 求解线性最小二乘问题的豪斯荷尔德变换法 3．15 求解线性最小二乘问题的广义逆法 3．16 病态方程组的求解 (3.1 system of linear equations class designs 3.2 to choose the principal element gaussian elimination 3.3 to elect principal element Gauss- when approximately the elimination 3.4 duplicate coefficient equation sets all choose the principal element gaussian elimination 3.5 duplicate coefficient equation sets to elect principal element Gauss- when approximately the elimination 3.6 solve three diagonal line equation sets to pursue the law 3.7 common belt equation set s solution 3.8 solution symmetrical equation set s resolution 3.9 solution symmetrical Zhengding equation set s square root method 3.10 solution large-scale sparse equation set to elect principal element Gauss- when approximately the elimination 3.11 solutions hold the Belize equation set s row article to abdicate House Holland who method 3.12 Gauss- the Seydell repetitive process 3.13 solution symmetrical Zhengding equation set s conjugate gradient method 3.14 solution linearity is smallest two rides the questionThe German m)

KPCA是一种非线性的盲源分离方法，很好用，推荐大家下载！(KPCA is a nonlinear blind source separation methods, very good, and recommend everyone to download!)