搜索资源列表
nihe4
- 四次及四次以下多项式拟和程序,可在c或c++环境下运行-Polynomial fit arithmetic witch could been run in C or C++ environment
2296_Regression
- Polynomial fit functions === === RegressionObject.cls contains a class that provides an easy way to add polynomial regression functionality to any application. If you just want linear regression or a very high degree, no matter: this class ha
PolyFitSingle
- //=== === === === === === === = //函数说明 //函数名称：PolyFit //函数功能：最小二乘法曲线拟合 //使用方法：double *x ---- 存放n个数据点的X坐标 // double *y ---- 存放n个数据点的Y坐标 // int n -------- 给定数据点个数 // double *a ---- 返回m-1次拟合多项式的m个系数 // int m -------- 拟合多项式的项数，即拟合多项式的
MSC
- PRINCIPLE: Each spectrum is shifted and rotated so that it fits as closely as possible to the mean spectrum of the data.The fit is achieved by LS (first-degree polynomial).
excel_in_civil_egineering
- 工量预测.xls 截面扭转特性.xls 截面特性一.xls 截面特性二.xls 最优化问题.xls 最值问题.xls 牛顿法解方程.xls 矩阵运算.xls 线性拟合.xls 解线性方程组.xls 解线性方程组（二）.xls 辛普森法积分.xls 频率与振型求解.xls 双变量模拟运算.xls 多元线性回归.xls 多项式拟合.xls 实例1.xls 实例2.xls 实例3.xls
orthofit
- ORTHOFIT Fit polynomial to data. YS = ORTHOFIT[X,Y,N] smooths/fits data Y[X] in a least-squares sense using a polynomial of degree N and returns the smoothed data YS.
fit
- 该算法是用正交多项式来求最小二乘拟合多项式。-This algorithm is to use orthogonal polynomials to seek least-squares polynomial fitting.
fit
- Matlab中提供了一种快速实现多项式拟合的方法函数polyfit()函数， 其格式：p=polyfit(x,y,n)其中x，y为样本向量，n为拟合的多项式的项数。下面拟f(x)=sinx+x,在区间【-3,3】上以0.5为间隔进行拟合。-Matlab provides a fast way to achieve polynomial fitting function polyfit () function, The format: p = polyfit (x, y, n) where
interpolating-method
- 线性插值，拉格朗日插值，多项式插值，二次多项式插值-Piecewise-Linear Fit.C Quadratic Polynomial Fit.C Polynomial Fit.C Condition Number of Vandermonde Matrix Lagrange Interpolating Polynomials
POLYNOMIAL-LEAST-SQUAR-FIT
- 多项式拟合程序，c语言版。拟合空间是n次多项式空间。分为子程序和主程序。并含有一个算例，以帮助理解。-Polynomial fitting procedures, c language version. Space is the n-th polynomial fitting space. Divided into subroutines and the main program. And contains a numerical example to help understand.
The-order-of-the-polynomial-fitting
- 我们处理数据时，往往需要事先知道这些数据的规律（如线性），然后再进行相应阶数的最小二乘法拟合，本文试图在不知道拟合阶数的情况下通过程序计算拟合阶数。-We handle the data, the data often need to know in advance the rules (such as linear), and then make the appropriate order of the least squares fit, this article attempts to f
curvefit
- 用最小二乘法进行曲线拟合. 用p－1 次多项式进行拟合，p<= 10 x,y 的第0个域x[0],y[0],没有用，有效数据从x[1],y[1] 开始 nNodeNum,有效数据节点的个数。 b,为输出的多项式系数，b[i] 为b[i-1]次项。b[0],没有用。 b,有10个元素ok-Using least squares curve fitting. With p-1 order polynomial fit, p <= 10 x, y 0 of
zuixiaoercheng
- 数值分析中最小二乘法拟合任意次多项式，已经运行过，放心下载！-Numerical analysis method of least squares polynomial fit any number of times, it has been run over, rest assured download!
quxiannihe
- 对于已知少量的点，使用多项式对其曲线进行近似拟合，从而预测未知的点的函数值。-For a small number of the known points, its curve is approximated using a polynomial fit to the prediction function value of the unknown point.
exponfit
- MATLAB不提供现成指数拟合函数，一方面由于但可以轻松通过多项式拟合转化而来，但是使用上还是不如有一个函数方便，所以特写这样一样简单实用的函数-MATLAB does not provide ready-exponential fit function, by hand because it can be easily transformed a polynomial fit, but still not as good as there is easy to use a function,
sourse
- 可以进行超定方程的求解，得到的是拟合的多项式，可以设置输入，决定多项式的次数-Overdetermined equations can be solved to obtain the polynomial fit, you can set the input, determine the number of polynomials
Least_squares_fitting_curve
- 使用最小二乘的方法进行拟合曲线，可进行二阶/三阶多项式拟合-fitting curve by Least squares,can make second-order/third-order polynomial fit
snv-(2)
- 对数据进行预处理，使用五阶多项式拟合和snv对数据进行预处理。-Preprocessing of the data, and use the fifth-order polynomial fit snv preprocessing of the data.
Polynomial of best-fit
- 最佳拟合多项式函数(Polynomial of best-fit)
多项式拟合的光伏电池阵列模拟器研究与设计
- 设置最大拟合误差和拟合模型实现对一组数据的拟合，克服了人工分段造成的主观误差(The maximum fitting error and fitting model are set up to fit a set of data, and the subjective error caused by artificial segmentation is overcome.)