FDTD

程序设计的一些基本算法 及其应用 有很高的应用价值(Some basic programming algorithm and its application has a high value)

说明：  对该模型参数辨识采用递推最小二乘法，即 RLS（ recurisive least square）， 它是一种能够对模型参数进行在线实时估计的辨识方法。(The recursive least square method is used to identify the parameters of the model, that is, rls (recurisive least square), which is an online real-time estimation method for the model parameters)

文件1.f90：生成翼型naca0012的椭圆网格，并计算流场，给出壁面压力分布 文件2.f90：maccormack方法解一维burger s方程 文件3.f90：解一维laval管流动，其进出口均为亚音速，喉道后部有激波(File 1.f90: generate the airfoil naca0012 elliptical rotary cell, and calculate the flow field, given the wall pressure distribution file 2.f90: maccormack method to solve the burger' s equation, one-dimensional file 3.f90: solution of one-dimensional laval tube flow, its progress exports are subsonic, the back of the throat have shock)

正则化方法包括Tikhonov，tsvd,ttls,tgsvd,csvd(Regularization Method include Tikhonov，tsvd,ttls,tgsvd,csvd.)

混合高斯分布的em算法，e步和m步，输出各参数值(mixture of gaussian,em)

读入红细胞图片，通过中值滤波，开运算算，闭运算，和贴标签等方法获得细胞个数 (Read into the red blood cell picture, opening operation count median filtering, and closing operation, and the labeling methods such as cell number)

based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to the minimum representation error. While the importance of sparsity is much emphasized in SRC and many related works, the use of collaborative representation (CR) in SRC is ignored by most literature.

研究典型相关分析的各种线性算法和非线性算法，并通过实验数据的比较说明了它们各自的特点(Canonical Correlation Analysis Study of the various linear and nonlinear algorithms algorithms, and through comparison of experimental data shows the characteristics of their respective)

自己编写的变步长龙格库塔方法解强非线性微分方程(their preparation variable step Changlong lattice-Kutta method to solve nonlinear differential equations)

一个用于复杂网络研究中计算网络静态参数（度分布，簇系数等）的c程序（其中的数据是具体的可换成其他的数据）。很简单但是对于做复杂网络研究的却很有启发的哦。(a complex network for research computing network static parameters (distribution, Clustering coefficient, etc.) c (which is specific data can be replaced by other data). Very simple but so complex network of research is very enlightening oh.)