搜索资源列表
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用matlab编的最小二乘法拟合的GUI程序,可以实现最小二乘法的计算-Matlab made by the least squares fitting procedure of the GUI, you can achieve the least square method of calculation
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Explanation on the least square line fitting algorithm.
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最小二乘法、最佳均方逼近、随机拟合及其MATLAB程序-Least square method, the best mean square approximation, random process fitting and MATLAB
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可以进行最小二乘法拟合和多项式拟合!其他还有误差相关数据分析。-Can least square fitting and polynomial fitting! Others include the error related to data analysis.
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用VB实现最小二乘法拟合曲线的功能,可以帮助一般的曲线绘制。-VB achieved by least square fitting curve of the features that help the general Curve.
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用C#编写的多元线性回归的最小二乘法,实现曲线的拟合~~
-Written in C# using multiple linear regression least square method, fitting a curve ~ ~
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用切比雪夫多项式逼近已知函数
用勒让德多项式逼近已知函数
用帕德形式的有理分式逼近已知函数
用列梅兹算法确定函数的最佳一致逼近多项式
求已知函数的最佳平方逼近多项式
用傅立叶级数逼近已知的连续周期函数
离散周期数据点的傅立叶逼近
用自适应分段线性法逼近已知函数
用自适应样条逼近(第一类)已知函数
离散试验数据点的多项式曲线拟合
离散试验数据点的线性最小二乘拟合
离散试验数据点的正交多项式最小二乘拟合
-By using Chebyshev poly
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最小二乘法拟合曲面,拟合效果很好,精度很高-Least squares fitting, fitting good effect, high accuracy
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VB采用最小二乘法演示如何在VB中实现线性拟合和二次拟合。-VB using the least square method demonstrates how to implement linear and two order curve fitting in VB.
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最小二乘法,用于拟合一组离散的点以得到目的曲线的方程。简单好用!-
Least squares method of least square, for the purpose of fitting a discrete set of points to get curve equation. Simple to use!
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最小二乘法实现的直线拟合,非常实用,简单易懂,C语言程序-Least square method to realize the linear fitting, very practical, straightforward, C language program
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最小均方误差(MMSE)的算法,利用最小二乘法进行拟合多元非线性方程,光纤无线通信系统中传输性能的研究。- Minimum mean square error (MMSE) algorithm, Multivariate least squares fitting method of nonlinear equations, Fiber Transmission wireless communication system performance.
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利用最小二乘法进行拟合多元非线性方程,微分方程组数值解方法,最小均方误差等算法的MSE的计算。- Multivariate least squares fitting method of nonlinear equations, Numerical solution of differential equations method, Minimum mean square error MSE calculation algorithm.
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切比雪夫 用切比雪夫多项式逼近已知函数
勒让德 用勒让德多项式逼近已知函数
帕德 用帕德形式的有理分式逼近已知函数
lmz 用列梅兹算法确定函数的最佳一致逼近多项式
ZJPF 求已知函数的最佳平方逼近多项式
方舟子 用傅立叶级数逼近已知的连续周期函数
事实上的部队 离散周期数据点的傅立叶逼近
SmartBJ 用自适应分段线性法逼近已知函数
SmartBJ 用自适应样条逼近(第一类)已知函数
multifit 离散试验数据点的多项式曲线拟合
LZXEC 离散
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通过最小二乘法进行平面拟合 平面拟合算法,鲁棒性非常好-Least square plane fitting algorithm
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用最小二乘法拟合二元多次曲线
已知点的x坐标集合
已知点的y坐标集合
已知点的个数方程的最高次
二元多次线性方程拟合曲线(Fitting two yuan multiple curves with least square method
X coordinate set of known points
Y coordinate set of known points
The highest degree of the equation of the number of known points
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扩展卡尔曼滤波EKF 去偏转换卡尔曼滤波CMKF 最小二乘拟和的方法(Extended kalman filter and EKF to partial transformation of kalman filtering CMKF least-square fitting and method)
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频域加权最小二乘拟合,加速度计动态模型参数辨识(Frequency domain weighted least square fitting)
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最小二乘法拟合直线,通过点云或者三角网格(Least square fitting straight line by point cloud)
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通过已有的点云数据或者三角网格数据最小二乘拟合圆柱面(Least square fitting cylinder by point cloud or tri-mesh)
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