FAST IDENTIFICATION OF LINEAR SYSTEMS IN THE PRESENCE OF INPUT AND OUTPUT NOISES

机译：存在输入和输出噪声时线性系统的快速识别

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This paper proposes a fast identification method for linear systems in the presence of input and output noises. The proposed method entails a new scheme that makes use of added information regarding the identified system so that a better estimate of the unknown variances of the input and output noises can be attained in a quicker manner during the iterative estimation process. Simulations described in the paper demonstrate that the proposed method can converge at a faster rate towards the true system parameters and the accuracy of the parameter estimates can also be raised.

机译：本文提出了一种存在输入和输出噪声的线性系统快速识别方法。所提出的方法需要一种新方案，该方案利用有关已识别系统的附加信息，以便可以在迭代估计过程中以更快的方式更好地估计输入和输出噪声的未知方差。本文中描述的仿真表明，所提出的方法可以以更快的速率收敛到真实的系统参数，并且还可以提高参数估计的准确性。

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来源
《2002 6th International Conference on Signal Processing Proceedings (ICSP'02) Vol.1; Aug 26-30, 2002; Beijing, China》|2002年|p.9-12|共4页
会议地点 Beijing(CN);Beijing(CN)
作者
Wei Xing Zheng;
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作者单位

School of Quantitative Methods and Mathematical Sciences University of Western Sydney Penrith South DC NSW 1797, Australia;

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原文格式 PDF
正文语种 eng
中图分类无线电电子学、电信技术;
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2. Proportionate NLMS With Unbiasedness Criterion for Sparse System Identification in the Presence of Input and Output Noises [J] . Wentao Ma, Dongqiao Zheng, Xiangqian Tong, Circuits and Systems II: Express Briefs, IEEE Transactions on . 2018,第11期

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3. Least-squares estimation of input/output models for distributed linear systems in the presence of noise [J] . J. S. Gibson, G. H. Lee, C. -F. Wu Automatica . 2000,第10期

机译：存在噪声时分布式线性系统输入/输出模型的最小二乘估计
4. Fast identification of linear systems in the presence of input and output noises [C] . Wei Xing Zheng . 2002

机译：在存在输入和输出噪声的情况下快速识别线性系统
5. Frequency Domain System Identification of Linear Time-Invariant Single-Input Single-Output 2-Dimensional Systems and Multi-Input Multi-Output 1-Dimensional Systems by Utilizing AFD Type Algorithms [D] . Wang, Xiaoyin. 2020

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6. Probability-based nonlinear modeling of neural dynamical systems with point-process inputs and outputs [O] . Roman Sandler, Dong Song, Robert E Hampson, 2014

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7. An Algorithm for Identification of Single-Input Single-Output Linear Systems with Estimation of Variance of Input-Output Noises [O] . Nobuo Komatsu 2014

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8. Adaptive Control of a Class of MIMO Nonlinear Systems in the Presence of Additive Input and Output Disturbances [R] . Tatlicioglu, E., Xian, B., Dawson, D. M., 2009

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FAST IDENTIFICATION OF LINEAR SYSTEMS IN THE PRESENCE OF INPUT AND OUTPUT NOISES

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