搜索资源列表
polynomial model
- 使用多项式拟合非线性曲线，对多项式系数进行参数辨识(The polynomial coefficients are identified by using polynomial fitting nonlinear curves.)
ellipse
- 使用matlab编程，用椭圆方程拟合非线性方程，以最小二乘法辨识。(Matlab programming, the elliptic equation fitting nonlinear equation, with least square identification.)
NIHE
- 这是自己修改过的实际matlab曲线拟合程序，可实现3阶最小二乘拟合(This is the actual Matlab curve fitting program which can realize the 3rd order least squares fitting)
nihe
- 对实际测得坐标实现圆拟合，前提是几何形状近似圆(The actual measure coordinates are fit to a circle, provided that that geometry approximates the circle)
polyfit
- 根据c代码修改的多项式拟合代码，未调用python第三方库，手打(Polynomial_python:function.According to the polynomial fitting code modified by c code, the python third-party library is not called.)
MATLAB 求最小二乘法系数
- 用MATLAB进行三次曲线的拟合，并运用最小二乘法求各个系数，得出曲线方程(The three curves are fitted with MATLAB, and the coefficients are obtained by using the least square method, and the curve equation is obtained.)
思维进化算法优化BP神经网络——非线性函数拟合
- 思维进化算法优化BP神经网络——非线性函数拟合，有源程序和数据(BP Neural Network Optimized by Mind Evolutionary Algorithm - Nonlinear Function Fitting)
MATLAB
- 利用matlab程序，进行曲线拟合，并返回误差R值(Matlab program, curve fitting, and return error R value)
BP拟合
- matlab图形怎么中文说明要这么多，不就是个拟合的算法简单应用(matlab Matlab graphics how Chinese instructions so much, is not a fitting algorithm, simple application.)
打包matlab文件
- 屏幕缺陷检测背景纹理拟合，用于LED mura缺陷检测(for p=1:1 [X,Y,Z]=random_point(img,0.5); C=coeffi(X,Y,Z); background=form(img,C); IMG=im2double(img); defect=IMG-background; img=defect; end defect=abs(defect); figure(2),imshow(img,[]),title('');)
边缘连接和线段拟合
- 线段和边缘连接拟合程序，可根据其中各自研究方向对内容自行修改，(Segment and edge connection fitting procedures, which can be modified on the basis of their respective research directions.)
实验2
- 最小二乘法详细程序实现。曲线拟合。 1.直线型 2.多项式型 3.分数函数型 4.指数函数型 5.对数线性型 6.高斯函数型(The principle of least square method, formula deduction, program realization.)
Maple化学反应速率方程参数拟合与回归分析
- Maple化学反应速率方程参数拟合与回归分析(Parameter fitting and regression analysis of Maple chemical reaction rate equation)
第三题程序和结果
- 用rstool进行多变量非线性拟合 题目：问题3：在某地夏天室内环境下，使用可变环境因素（干球温度、相对湿度及风速）与体感温度（红字）对照表（见表3）中的数据作为数据源，请挖掘出可变环境因素与体感温度之间的关系，并进行误差分析。 表3可控环境因素对体感温度对照表 干球温度℃ 相对湿度% 风速FPM(1FPM=0.00508m/s) 0 100 200 300 400 500 35 30 35 31.6 26.1 23.8 22.7 22.2 40 35 31.9 26.4 24
we
- RBF 神经网络用于函数拟合，便于进一步的rbf分析建模，高斯基函数的求取(RBF neural network is used for function fitting to facilitate further RBF analysis modeling and gauss function.)
Desktop
- 主要用于三次样条拟合，对离散点进行拟合插值，(Three order spline fitting)
多项式拟合批处理代码
- matlab多项式拟合批量处理代码实现，可做参考(Matlab polynomial fitting batch processing code, can be used as reference.)
椭球拟合
- 根据三维坐标拟合椭球面 基于非线性最小二乘法(Ellipsoid fitting based on 3D coordinates based on nonlinear least squares method)
zernike
- 计算泽尼克多项式和具有一致相合函数的泽尼克拟合系数(Zernike polynomials are orthogonal on the unit circle and are commonly used in optics for phase aberrations. Use zernike_fcn3.m to generate Zernike polynomials. Input includes a vector of the desired polynomials; these do n
PI实现
- 基于改进的PI模型对非线性曲线进行拟合，二次寻优算法进行参数辨识，用逆模型前馈补偿(classical PI modeling)