The filtering based maximum likelihood recursive least squares estimation for multiple-input single-output systems

Feiyan Chen; Feng Ding

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The filtering based maximum likelihood recursive least squares estimation for multiple-input single-output systems

机译：多输入单输出系统基于滤波的最大似然递推最小二乘估计

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摘要

In this paper, we use a noise transfer function to filter the input-output data and propose a new recursive algorithm for multiple-input single-output systems under the maximum likelihood principle. The main contributions of this paper are to derive a filtering based maximum likelihood recursive least squares (F-ML-RLS) algorithm for reducing computational burden and to present two recursive least squares algorithms to show the effectiveness of the F-ML-RLS algorithm. In the end, an illustrative simulation example is provided to test the proposed algorithms and we show that the F-ML-RLS algorithm has a high computational efficiency with smaller sizes of its covariance matrices and can produce more accurate parameter estimates.

机译：在本文中，我们使用噪声传递函数对输入输出数据进行滤波，并在最大似然原理下针对多输入单输出系统提出了一种新的递归算法。本文的主要贡献是推导了一种基于滤波的最大似然递归最小二乘（F-ML-RLS）算法，以减轻计算负担，并提出了两种递归最小二乘算法以展示F-ML-RLS算法的有效性。最后，提供了一个仿真示例来测试所提出的算法，并且我们表明F-ML-RLS算法具有较高的计算效率，并且协方差矩阵的大小较小，并且可以产生更准确的参数估计。

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来源
《Applied Mathematical Modelling》 |2016年第3期|2106-2118|共13页
作者
Feiyan Chen; Feng Ding;
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作者单位

Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, PR China;

Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, PR China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
System identification; Least squares; Maximum likelihood; Data filtering; Multiple-input systems;

机译：系统识别;最小二乘;最大似然;数据过滤多输入系统;

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The filtering based maximum likelihood recursive least squares estimation for multiple-input single-output systems

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