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Mathematics > Statistics Theory

arXiv:2506.00984 (math)
[Submitted on 1 Jun 2025 ]

Title: A Quantized Order Estimator

Title: 量化阶数估计器

Authors:Lida Jing
Abstract: This paper considers the order estimation problem of stochastic autoregressive exogenous input (ARX) systems by using quantized data. Based on the least squares algorithm and inspired by the control systems information criterion (CIC), a new kind of criterion aimed at addressing the inaccuracy of quantized data is proposed for ARX systems with quantized data. When the upper bounds of the system orders are known and the persistent excitation condition is satisfied, the system order estimates are shown to be consistent for small quantization step. Furthermore, a concrete method is given for choosing quantization parameters to ensure that the system order estimates are consistent. A numerical example is given to demonstrate the effectiveness of the theoretical results of the paper.
Abstract: 本文研究了利用量化数据估计随机自回归外生输入(ARX)系统的阶次问题。 基于最小二乘算法,并受控制系统的信息准则(CIC)的启发,针对带有量化数据的ARX系统提出了一种新的准则,以解决量化数据的不准确性问题。当系统阶次的上界已知且满足持久激励条件时,证明了对于小的量化步长,系统阶次估计是一致的。此外,给出了选择量化参数的具体方法,以确保系统阶次估计的一致性。最后通过一个数值例子验证了本文理论结果的有效性。
Subjects: Statistics Theory (math.ST)
Cite as: arXiv:2506.00984 [math.ST]
  (or arXiv:2506.00984v1 [math.ST] for this version)
  https://doi.org/10.48550/arXiv.2506.00984
arXiv-issued DOI via DataCite

Submission history

From: Lida Jing [view email]
[v1] Sun, 1 Jun 2025 12:35:40 UTC (519 KB)
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