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RLS最小二乘改进算法，能够根据输入输出数据辨识系统参数-Least Squares RLS improved algorithm, the system parameters according to the identification of the input and output data
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matlab实现自适应滤波，分别用LMS算法和RLS算法实现系统辨识问题。-matlab adaptive filter, LMS algorithm and RLS were used algorithms for system identification problems.
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参数辨识问题，本程序是基于RLS法的参数辨识最新解法-Based on the RLS parameter identification
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系统辨识中最小二乘法的RLS算法MATLAB实现-System identification least squares RLS algorithm based on MATLAB realization
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对于一阶系统辨识，分别采用LMS、RLS、仿射投影算法来估计参数-For a first-order system identification, respectively, using LMS, RLS, affine projection algorithm to estimate the parameters
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系统辨识中最小二乘辨识的系列方法函数接口，包括LS，RLS，RELS，IV，GLS等，提供一种数据测试实例。-Series function interface system identification method of least squares identification, including LS, RLS, RELS, IV, GLS, etc., to provide a test case data.
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the linear ARX model as shown below [12] is used to represent the input and the output data for the system. This ARX model is utilized for both Least Square (LS) and Recursive Least Square (RLS) algorithms. It is one of the simplest statistical metho
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利用矩阵最小二乘的辨识结果作为递归最小二乘的初值，进行系统辨识-Identification using matrix least squares RLS as a result of the initial value, system identification
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系统辨识与自适应控制递推最小二乘估计（RLS）及模型阶次辨识（F-Test）-System identification and adaptive recursive least square estimation (RLS) and model order identification (F-Test) for system identification and adaptive control
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最小二乘法是系统辨识中最经典的方法，它通过最小化误差的平方和寻找数据的最佳函数匹配。利用最小二乘法可以简便地求得未知的数据，并使得这些求得的数据与实际数据之间误差的平方和为最小。最小二乘法还可用于曲线拟合。其他一些优化问题也可通过最小化能量或最大化熵用最小二乘法来表达。其中，RLS是递推最小二乘法程序，ELS是增广递推最小二乘法的程序。-
System identification least squares method is the most classic method, which
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好用的,系统辨识中,递推最小二乘估计RLS是辨识模型阶次的一个重要的算法,(Easy-to-use, system identification, the recursive least squares estimate RLS times of order identification model is an important part of the algorithm,)
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对该模型参数辨识采用递推最小二乘法，即RLS（ recurisive least square），它是一种能够对模型参数进行在线实时估计的辨识方法(parameter identification)
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递推最小二乘参数辨识，适用于ARMA模型，锂电池等效电路模型参数辨识时使用(RLS for parameter identification)
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