A Unified Recursive Identification Algorithm with Quantized Observations Based on Weighted Least-Squares Type Criteria

This paper investigates system identification problems with Gaussian inputs and quantized observations under fixed thresholds. By reinterpreting the nonlinear effects induced by quantization as the product of the unknown parameter and an unknown nonlinear coefficient, this work establishes a novel w...

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Vydáno v:	IEEE transactions on automatic control s. 1 - 16
Hlavní autoři:	Liu, Xingrui, Wang, Ying, Zhao, Yanlong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	IEEE 2025
Témata:	Accuracy Approximation algorithms Convergence convergence analysis Gaussian inputs Heuristic algorithms Linear systems Noise measurement Prediction algorithms quantized observations Stochastic processes System identification Vectors weighted least-squares
ISSN:	0018-9286, 1558-2523
On-line přístup:	Získat plný text
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