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The module LSQ is for unconstrained linear least-squares fitting. It is
based upon Applied Statistics algorithm AS 274 (see comments at the start
of the module). A planar-rotation algorithm is used to update the QR-
factorization. This makes it
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使用Marquardt方法的非线性嘴小二乘拟合算法-use of small mouth nonlinear least square fitting algorithm
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采用最小二乘法进行多点平面拟合的算法介绍。,Least square method for planar multi-point fitting algorithm introduction.
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强局部加权回归算法由Cleveland[7]提出,主要利用局部观测数据对欲拟合点进行多项式加权拟合,并用最小二乘法进行估计.它综合了传统的局部多项式拟合,局部加权回归以及具有强鲁棒性的拟合过程
-Strong locally weighted regression algorithm by Cleveland [7] proposed, mainly using local observational data points on the polynomial fitting For wei
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最小二乘拟合算法C程序,N为拟合点数,T为拟合阶数。-Least-squares fitting algorithm C procedures, N for the fitting points, T for the fitting order.
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Explanation on the least square line fitting algorithm.
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利用最小二乘算法对一组坐标进行曲线拟合,其中包含了利用直接LU分解法解方程的算法代码实现。希望对用到数值计算的带来帮助。-The least square algorithm for fitting a set of coordinates, including the use of direct LU decomposition equations for the algorithm code to achieve. Want to use to bring numerical help.
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用最小二乘法,在已知函数点x0,x1……xn的函数值y0,y1……yn的情况下,求拟合多项式-The least square method, the known function points x0, x1 ... ... xn of the function values y0, y1 ... ... yn circumstances, find fitting polynomial
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在VC++6.0环境下编写的一个最小二乘算法,可以对任意幂数的五个点进行曲线拟合-Written in vc++ 6.0 environment,it is a least-square algorithm of arbitrary power, it can the number of curve fitting five points
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最小 二乘拟合算法。移植性性一般不过也可以互相学学的-The least square fitting algorithm. Portability is generally but also can learn each other I
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Matlab实现最小二乘拟合.要求输入拟合点,输出拟合函数的系数并在同一坐标系下画出离散点和拟合曲线。-matlab has given a least square fitting algorithm.and given combine curve.
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non linear least square data fitting algorithm
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阵元失效会破坏拖曳线列阵的幅相分布,导致阵列的旁瓣级出现明显升高,严重影响了阵列的性能。阵元失效条件下
的波束形成是一个非线性的最小平方的优化问题,对其直接求解非常困难。针对这一情况,提出了一种基于遗传算法的阵元
失效校准方法。算法的基本思想是将失效阵元的权重强制为零,并使得阵列的实际响应与期望响应在主瓣区域相匹配,同时
对阵列响应的旁瓣级作出限制-Failed elements will des仃oy the amplitude and phase distribution and
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chebyshev算法,曲线拟合最小二乘法,还有数值分析课本中的一些算例,简便了计算过程,提高了运算效率-Chebyshev algorithm, curve fitting least square method, and some examples of numerical analysis of textbooks, simple calculation process, improve the operation efficiency
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利用最小二乘法进行拟合多元非线性方程,通过反复训练模板能有较高的识别率,最小均方误差(MMSE)的算法。- Multivariate least squares fitting method of nonlinear equations, Through repeated training YcQJZVVlate have higher recognition rate, Minimum mean square error (MMSE) algorithm.
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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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基于统计学方法圆拟合曲线,最小二乘圆拟合算法。-Circle Fitting Curve Based on Statistical Method,Least square circle fitting algorithm。
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递推最小二乘拟合算法 用于实时拟合时间序列ARMA模型参数 例如 陀螺仪随机噪声 股票 交通等模型的参数拟合(Recursive least square fitting algorithm is used to fit the parameters of time series ARMA model, such as gyroscope, random noise, stock traffic and so on)
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对于单输入单输出的系统(Single input single output,SISO)常采用最小二乘方法辨识系统的参数。最小二乘参数估计是一个经典的方法,概念简明,适应范围广,来源于数理统计的回归分析,它能提供一个在最小方差意义上与实验数据最好拟合的模型,在一些情况下,可得到与极大似然法一样好的统计效果,并能很方便地与其它辨识算法建立关系。在一定条件下,最小二乘法参数估计法有最佳的统计特性,即一致的、无偏的和有效的结果。本代码主要关于使用递推最小二乘辨识方法与增广最小二乘辨识方法辨识模型参数,
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利用基于最小二乘法的多项式拟合算法处理商业数据,包含源码(Using the polynomial fitting algorithm based on the least square method to deal with commercial data, including the source code)
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