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Description: 用得到的已知输入输出数据，通过编好的渐消记忆增广最小二乘辨识软件辨识已知系统的阶次与估计其参数，验证所编软件的正确性-known to be useful input and output data, through the provision of good memories fading by the least square identification software widely known identification system and the order of the estimated parameters, develops software to certify the correctness
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Size: 95305 |
Author: 丁学明 |
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Description: 这是黑龙江大学自控理论杨易朋同学在最优估计课程当中用matlab编写的递推增广最小二乘算法!-This is the theory of Heilongjiang University, Yang Yi-controlled peer students in courses optimal estimate prepared by using Matlab recursive least squares algorithm to broaden!
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Size: 824 |
Author: 杨易朋 |
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Description: 用得到的已知输入输出数据，通过编好的渐消记忆增广最小二乘辨识软件辨识已知系统的阶次与估计其参数，验证所编软件的正确性-known to be useful input and output data, through the provision of good memories fading by the least square identification software widely known identification system and the order of the estimated parameters, develops software to certify the correctness
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Size: 95232 |
Author: 丁学明 |
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Description: 这是黑龙江大学自控理论杨易朋同学在最优估计课程当中用matlab编写的递推增广最小二乘算法!-This is the theory of Heilongjiang University, Yang Yi-controlled peer students in courses optimal estimate prepared by using Matlab recursive least squares algorithm to broaden!
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Size: 1024 |
Author: 杨易朋 |
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Description: 为了改善噪声e(k)为有色噪声模型的系统参数估计的统计特性，提出了一种增广矩阵的方法，称为增广最小二乘算法，MATLAB实现范例-In order to improve the noise e (k) for the colored noise model of the system parameters estimated statistical characteristics, an Augmented Matrix method, called Augmented Least Squares, MATLAB implementation examples
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Size: 1024 |
Author: 冷强 |
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Description: 系统参数辨识，用增广最小二乘算法实现。对书中的程序进行了改进：由于噪声是未知的，虽然我们模拟了系统的随机白噪声，但进行辨识时必须对噪声进行估计，见程序45行和53行。-System parameter identification, with the extended least squares algorithm. Procedures for improving the book: Because the noise is unknown, although we simulate a system of random white noise, but to identify the noise must be estimated, see the program of 45 lines and 53 lines.
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Author: 王京 |
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Description: 自适应控制中，用Matlab算法实现增广递推最小二乘参数估计-Adaptive control, augmented with Matlab algorithm recursive least squares parameter estimation
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Size: 24576 |
Author: xiajulong |
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Description: 系统辨识与自适应控制中----递推增广最小二乘参数估计算法-Augmented recursive least squares parameter estimation
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Size: 1024 |
Author: 周武 |
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Description: matlab实现：①递推增广最小二乘参数估计（RELS）②确定性系统的递推梯度校正参数估计（RGC）③递推最小二乘参数估计（RLS）④递推极大似然参数估计（RML）⑤递推随机牛顿参数估计（RSNA）-Matlab: (1) augmented recursive least square parameters estimation (RELS) (2) of a deterministic system recursive gradient correction parameter estimation (RGC) (3) recursive least squares (RLS) (4) parameter estimation, the recursive maximum likelihood parameter estimation (RML) (5) recursive random Newton parameter estimation (RSNA)
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Size: 4096 |
Author: 张启 |
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Description: 增广最小二乘的递推算法对应的噪声模型为滑动平均噪声，扩充了参数向量和数据向量H（k）的维数，把噪声模型的辨识同时考虑进去。最小二乘法只能获得过程模型的参数估计，而增广最小二乘法同时又能获得噪声模型的参数估计，若噪声模型为平均滑动模型，，则只能用RELS算法才能获得无偏估计。当数据长度较大时，辨识精度低于极大似然法。-Augmented least squares of recursion algorithm corresponding noise model for moving average noise, expanded parameter vector and data vector H (k) of the dimension, the noise model identification and at the same time into consideration. Least square method can only obtain process model parameter estimation, and augmented least squares method at the same time can obtain noise model parameter estimation, if noise model for the average sliding model,, it can only use RELS algorithm to obtain unbiased estimation. When the data length is bigger, the identification accuracy is lower than maximum likelihood method.
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Size: 1024 |
Author: 张鹏 |
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Description: 提供了几种最小二乘法程序包括：批处理最小二乘参数估计，递推最小二乘参数估计，遗忘因子递推最小二乘参数估计，递推增广最小二乘参数估计。-Provides several least squares procedures include: Batch least squares parameter estimation, recursive least squares parameter estimation, forgetting factor recursive least squares parameter estimation, Recursive Extended Least Squares Parameter Estimation.
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Size: 3072 |
Author: 精木 |
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Description: test2:
一、 基本最小二乘法一次算法
二、 基本最小二乘法递推算法
三、 最小二乘遗忘因子一次完成算法
四、 最小二乘遗忘因子递推算法
五、 最小二乘限定记忆算法
六、 最小二乘偏差补偿算法
七、 增广最小二乘算法
八、 广义最小二乘算法
test3:
一、 辅助变量自适应滤波算法
二、 辅助变量纯滞后算法
三、 辅助变量Tally原理算法
四、 多级最小二乘算法
五、 各类改进最小二乘算法的特点
test4:
1、 第二类随机性辨识问题的梯度校正
2、 随机牛顿法
test5:
1、 递推的极大似然估计
2、 预报误差参数辨识
test6:
1、 根据Hankel矩阵秩估计模型阶次(弱噪声)
2、 根据Hankel矩阵秩估计模型阶次(强噪声)
3、 利用行列式比估计模型阶次（白噪声）
4、 利用行列式比估计模型阶次（有色噪声）
5、 利用残差的方差估计模型阶次（白噪声）
6、 利用残差的方差估计模型阶次（有色噪声）
7、 AIV定阶法（白噪声）
8、 AIV定阶法（有色噪声）
test7:
1、 一阶惯性+纯滞后环节-----两点法
2、 面积法1
3、 levy法
-test2:
First, the basic method of least squares algorithm once
Second, the basic recursive least squares algorithm
Third, once the forgetting factor least squares algorithm
Fourth, the forgetting factor recursive least squares algorithm
Fifth, the least-squares algorithm limited memory
Six , least squares error compensation algorithm
Seven , extended least squares algorithm
Eight , generalized least squares algorithm
test3:
An auxiliary variable adaptive filtering algorithm
Second, the auxiliary variable time delay algorithm
Third, the principle of auxiliary variable algorithm Tally
Fourth, multi-stage least squares algorithm
Fifth, the least squares algorithm to improve the characteristics of various types of
test4:
1, the second class of stochastic gradient identification problem corrected
2 , randomized Newton
test5:
1, the recursive maximum likelihood estimation
2, the prediction error parameter identification
test6:
1 , according to the Hankel matrix rank est
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Size: 445440 |
Author: yurong |
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Description: 它属于系统辨识与自适应控制程序。其功能是递推增广最小二乘参数估计（RELS）-It belongs to the system identification and adaptive control procedures. Its function is recursive extended least squares parameter estimation (RELS)
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Size: 1024 |
Author: lavi |
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Description: 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，采用高斯噪声作为系统的噪声。(For Single input Single output (SISO), the least squares method is used to identify the parameters of the system.
Least squares parameter estimation is a classic method, concept is concise, wide adaptation, derived from the regression analysis of mathematical statistics, it can provide a minimum variance sense the best fitting model with the experimental data, in some cases, the statistics can be obtained with the maximum likelihood method is as good effect, and can easily establish relations with other identification algorithm.
Under certain conditions, the least square parameter estimation method has the best statistical properties, namely consistent, unbiased and effective results.
This code mainly USES the method of recursive least squares identification method and the augmented least squares identification method to identify the model parameters, using gaussian noise as the noise of the system.)
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Size: 1024 |
Author: M.R.J.
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