列主元高斯消去法求解方程

有限元的分析程序，对于初学有限元在结构中的应用很好用-Finite element analysis program for learning the structure of finite element in the application of good use

有一个n*m的草坪(1

最小二乘法圆拟合，用于图像处理，比较复杂，请耐心看完，也可直接使用-least square error (LSE) circle fitting, applicable to image processing, a little complicated, can be used directly

这是灰色预测代码,一般灰色预测的参数需要应用到矩阵的运算,本代码通过对其变形,使其运算简单化.-This is a gray code forecast, Gray forecast general parameters applied to the needs of the matrix computation, the code through its deformation, it Operational simplistic.

数据挖掘中的一算法 ines算法 c下实现的。适合初学习数据挖掘者借鉴-data mining algorithms ines of an algorithm to achieve the c. Data for early learning from the dig

一个实用的雅可比迭代求根的C++源代码，可以很方便的进行计算，并且是由用户输入数据，很灵活。-Use of a Jacobi iteration Roots of C++ source code

能实现16位的快速傅立叶变化,位数可自由设定,输出斜波可调整个数-Can realize the fast Fourier 16 changes in the median can be free to set up, the output ramp adjustable number of

program compare files in 2 directories. argv[1/2] - folder_1/2, argv[3] - file with result

c语言简单算法实例-c algorithm example, simple language

用一观测器从t=1秒开始对一个运动目标的距离进行连续地跟踪测量，假设观测的间隔为一秒钟，雷达到运动目标之间的距离为S(t)（1） 统计特性的初值为 （2）观测误差是与和均不相关的白噪声序列，并且有 （3）观测数据存放在附加的文件中（单位：m）。 要求：分析上述对象，建立系统模型，构造卡尔曼滤波器，编程计算，求： （1） 距离S(t)的最佳估计及估计误差， （2） 距离S(t-5)的最佳平滑及估计误差， （3） 距离S(t+5)的最佳预测及估计误差， （4） 对结果进行分析讨论。 -By one observer from the t = 1 PST on a moving target tracking for distance measurement, assuming that the observation interval is one second, the radar that the distance between the moving target for the S (t) (1) the statistical characteristics of the initial condition (2) observational error is not associated with white noise sequence, and (3) observational data stored in the attached document (unit: m). Requirements: Analysis of the above-mentioned object, the establishment of the system model, constructed Kalman filter, programming terms, seeking: (1) distance from S (t) the best estimate and the estimation error, (2) distance from S (t-5) the most good smoothing and estimation error, (3) distance from S (t+ 5) t