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求算非线性最小二乘问题的经典算法。Levenberg-Marquardt算法。-This is levmar, a copylefted C/C++ implementation of the Levenberg-Marquardt non-linear
least squares algorithm. levmar includes double and single precision LM versions, both
with analytic and finite differ
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使用奇异值分解来帮助求解最小二乘问题，特别是在方程系数矩阵不满秩的情况下。-SGELSD computes the minimum-norm solution to a real linear least
* squares problem:
* minimize 2-norm(| b- A*x |)
* using the singular value decomposition (SVD) of A. A is an M-by-N
* matrix which
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matlab中编程实现的线性最小二乘拟合函数：
lzxec:功能：离散试验数据点的线性最小二乘拟合-matlab programming in a linear least-squares fitting function: lzxec: Function: discrete experimental data points, the linear least-squares fitting
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所谓偏最小二乘法，就是指在做基于最小二乘法的线性回归分析之前，对数据集进行主成分分析降维，下面的源码是没有删减的，GreenSim团队免费提供您使用，转载请注明GreenSim团队（http://blog.sina.com.cn/greensim）。 -The so-called partial least squares method, this means doing the least square method based on linear regression analysis pr
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卡尔曼于1960年提出了离散系统线性滤波的递推求解方法即卡尔曼滤波算法。该滤波算法是基于线性最小平方法的、进行有效递推计算的一组数学方程式,算法功能强大,支持对过去、现在和将来状态的估算。-Kalman in 1960 proposed a linear discrete-time systems to solve recursive filtering methods for the Kalman filter. The filtering algorithm is based on the
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4 files are included in the package:
(1) fs01.m - the 1st-order local linear approximation (LLA) very similar to algorithm by Farmer and Sidorowich (1987). Uses constrained linear least squares (lsqlin) and
(2) ts1.m - to reconstruct the vector
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Lm算法是非常有效的非线性最小二乘法，对于光束平差很有用-Lm algorithm is very effective non-linear least squares method is useful for beam adjustment
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有一些matlab的相关程序，也有M文件-linear least squares estimate
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Using least squaer algorithm, this code can do fitting curve for the measurement data
(linear ~ cubic )
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matlab 最小二乘线性回归 递推法 源码，解决线性回归中的病态方程问题-recursive least squares linear regression method matlab source code, solve the equation of linear regression of pathological problems
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SVD算法可用来求解大多数的线性最小二乘法问题.对矩阵进行奇异值分解。-SVD algorithm is used to solve most of the linear least squares problem. Of the matrix singular value decomposition.
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a QR decomposition (also called a QR factorization) of a matrix is a decomposition of the matrix into an orthogonal and an upper triangular matrix. QR decomposition is often used to solve the linear least squares problem, and is the basis for a parti
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本程序是GPS线性最小二乘定位算法matlab仿真程序，欢迎大家下载！-This procedure is linear least squares GPS positioning algorithm matlab simulation program, are welcome to download!
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fit_maxwell_pdf - Non Linear Least Squares fit of the maxwellian distribution.
given the samples of the histogram of the samples, finds the
distribution parameter that fits the histogram samples.
fits data to the probability of the form:
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项目采用matlab对强迫零均衡器、最小均方误差均衡器、自适应线性均衡器进行了编程实现，并给出了计算机的仿真结果以及对仿真结果的分析，最后，给出递归最小二乘准则下的均衡器仿真予以比较。-Forced to zero on the project using matlab equalizer, minimum mean square error equalizer, adaptive linear equalizer is programmed to achieve, and gives the
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一元线性回归方程， 求线性回归方程：Y = a + bx 的回归系数a和b. 用的是最小二乘法推导的结果。网上搜索最小二乘法原理，配合这个源代码学习还是不错的。本代码是网上搜来的，发现自学用不错，特上传分享。-Linear regression equation, find the linear regression equation: Y = a+ bx the regression coefficients a and b. derived using a least squares res
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最小二乘法 拟合函数 线性预测系统的实现-Linear least squares fitting function Forecasting System
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最小二乘法拟合一元线性回归函数，并进行显著性和拟合优度检验。-Least squares fit linear regression functions, and for significance and goodness of fit test.
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QR分解法是三种将矩阵分解的方式之一。这种方式，把矩阵分解成一个正交矩阵与一个上三角矩阵的积。QR 分解经常用来解线性最小二乘法问题。QR 分解也是特定特征值算法即QR算法的基础。-QR decomposition are the three ways of decomposition of the matrix. In this way, the matrix decomposition into an orthogonal matrix and an upper triangular mat
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正交线性最小方差评估a x + b y + c = 0-ORTHLLS2D returns the Orthogonal Linear Least Squares estimate for parameters of line a x+ b y+ c = 0
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