非线性最小二乘估计,nonlinear least squares estimation
1)nonlinear least squares estimation非线性最小二乘估计
1.To investigate the sensitivity of the traditional Newton methods widely used in the theory ofnonlinear least squares estimation(NLSE) in geodesic data processing to the initial point,an improved particle swarm optimization(PSO) algorithm is proposed.针对测量数据处理中非线性模型参数估计理论广泛使用的传统牛顿类算法对初值的敏感性问题,提出了一种求解非线性最小二乘估计的改进粒子群优化算法。
英文短句/例句
1.A Least Square Nonlinear Estimation of Cumulative Reserves Model累计储量模型的非线性最小二乘估计
2.Genetic Algorithms Research Based on Nonlinear Least Squares Estimation;非线性最小二乘估计的遗传算法研究
3.A New Method of Non-linear Least Square Estimation of Rheological Parameter for Drilling Fluid钻井液流变参数的非线性最小二乘估计算法
4.Consistency of the Least Squares Estimator in Nonlinear Regression Model;非线性回归模型中最小二乘估计量的相合性
5.Weighted Least Squares Estimate for Linear Regression Model;线性回归模型中的加权最小二乘估计
6.Relative Efficiencies of Least Squared Estimates in Linear Models线性模型中最小二乘估计的相对效率
7.Local Linear Estimation by Two Stages Least Square for Nonparametric Simultaneous Equation Models in Econometrics非参数计量经济联立模型的局部线性两阶段最小二乘估计
8.The Theoretical and Application Research on Nonlinear Semiparametric Model;非线性半参数模型最小二乘估计理论及应用研究
9.Some Necessary and Sufficient Conditions of The LSE and BLUE in Growth Curve Model;生长曲线最小二乘估计和最佳线性无偏估计相等的几个充要条件
10.Expansion on r-moment Consistency of the Lest Squares Estimator in Linear Regression;线性模型最小二乘估计相合性定理的推广
11.Proof of the uniqueness on the least square estimate for estimation in the linear models;线性模型参数最小二乘估计唯一性的一个证明
12.Moderate Deviations Principle and the Law of the Iterated Logarithm for LSE in Linear Models;线性模型中最小二乘估计的中偏差及重对数律
13.The Theory of Least Squares Estimation on Linear Model and It s Application;线性模型参数的最小二乘估计理论及其应用
14.The Related Efficiency of the Least Squares Estimator in Singular Model;奇异线性模型中最小二乘估计的相对效率
15.Inefficiency of the Least Squares Estimation in Singular Growth Curve Model;奇异增长曲线模型中最小二乘估计的有效性
16.THE SIMULATION ANALYSIS OF THE LEAST-SQUARES ESTIMATION IN MIXED LINEAR MODELS混合线性模型最小二乘估计的模拟分析
17.The Best Linear Unbiased Estimate of Parameter Matrix and Measures of Inefficiency of the Least Squares Estimate in Singular Growth Curve Model;奇异增长曲线模型中参数阵的最优估计及最小二乘估计的有效性
18.The Calculation of AOF of Gas Well Based on Non-linear Least Squares Method基于非线性最小二乘法的气井无阻流量计算
相关短句/例句
nolinear least square estimation method非线性最小二乘估计法
3)non-linear least square estimation method非线性最小二乘估计算法
4)Linear least square estimation线性最小二乘估计
5)nonlinear least square非线性最小二乘
1.Implementation ofnonlinear least square with global convergence in Forstat全局收敛的非线性最小二乘在Forstat中的实现
2.The Gauss-Newton method is applied to solve thenonlinear least square equations and a simple and applicable iterative formula is deduced, which is locally convergent and divergent sometimes.介绍了采用非线性最小二乘方法回归乙烯深度氧化反应动力学方程。
3.Through transferring solution procedure,the problem was inverted intononlinear least square optimization process with constraint conditions in two stages using function lambertw and function lsqnonlin.对生态学领域的高精度参数确定问题提出了一种解决方案,结合实例,利用肖维奈特准则进行回归分析筛选数据,利用MATLAB工具中vpa和dlmwrite函数来保证数据传递的精度,并变换求解格式利用lambertw函数和lsqnonlin函数将问题转化为带约束条件的非线性最小二乘两级优化过程加以解决。
6)nonlinear least squares非线性最小二乘
1.Algorithm ofnonlinear least squares adjustment of any planenetworks with coordinates computed automatically;任意平面网坐标自动解算的非线性最小二乘平差算法
2.A new newton iterative algorithm for solvingnonlinear least squares problem;一种新的求解非线性最小二乘问题的牛顿迭代算法
3.Unified model and ill-posed property of numerical iterative formula for solvingnonlinear least squares problem;非线性最小二乘问题数值迭代法的统一模型及其不适定性
延伸阅读
线性最小二乘估计以误差的平方和最小为准则根据观测数据估计线性模型中未知参数的一种基本参数估计方法。1794年德国数学家C.F.高斯在解决行星轨道预测问题时首先提出最小二乘法。它的基本思路是选择估计量使模型（包括静态或动态的，线性或非线性的）输出与实测输出之差的平方和达到最小。这种求误差平方和的方式可以避免正负误差相抵，而且便于数学处理（例如用误差的绝对值就不便于处理）。线性最小二乘法是应用最广泛的参数估计方法，它在理论研究和工程应用中都具有重要的作用，同时它又是许多其他更复杂方法的基础。线性最小二乘法是最小二乘法最简单的一种情况，即模型对所考察的参数是线性的。线性动态模型为yk＝xθ＋εk式中数据向量xk＝[yk-1，yk-2,...,yk-n，uk-1，uk-2,...，uk-n]T；参数向量θ＝[-a1,-a2,...,-an，b1,b2,...,bn]T；εk为误差；n为模型阶数；N为数据长度（N≥2n）。选择估计准则 使J为最小的参数估计，称为模型的线性最小二乘估计，用符号孌LS表示。可以得出 孌LS＝(XTX)-1XTY式中矩阵XT＝[xn+1，xn+2,...,xnn+N]；向量Y＝[yn+1，yn+2，...,ynn+N]T。孌LS是数据的线性函数，因此称为线性最小二乘估计。它的突出优点是：对于任何一组数据，只要孌LS存在，不要求了解误差序列{εk}的统计特性，便能按照J求出孌LS；算法很简单。孌LS存在的条件是矩阵(XTX)满秩,这要求{uk}为n阶持续激励输入。当误差序列{εk}是零均值的白噪声,并对输入、输出功率加以适当的限制时，孌LS是渐近无偏的强一致性估计,即当N →∞时,。但是对于有限的数据,上述结论不能成立,而且通常误差{εk}也不是白噪声,故一般情况下孌LS是有偏估计，这是它的缺点。为了克服这个缺点，可以采用其他改进的估计算法，例如广义最小二乘估计、辅助变量估计和极大似然估计等。上述单输入单输出系统的线性最小二乘估计算法还可推广到多输入多输出系统，并且有相应的递推估计算法。参考书目G.C.哥德温、R.L.潘恩著，张永光、袁震东译：《动态系统辨识：试验设计与数据分析》，科学出版社，北京，1983。(G.C.Goodwin and R.L. Payne，DynamicSystemIdentification: Experi-mentDesign and Data Analysis, Academic Press, NewYork,1977.)
