Recursive identification for FIR systems with interval binary observations

Xiaowen Liu; Xiaodong Li; Mingjie Shao; Yanlong Zhao

doi:10.1016/j.ifacsc.2026.100383

February 5, 2026IFAC Journal of Systems and Control

Recursive identification for FIR systems with interval binary observations

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Key Points

The recursive identification approach successfully models FIR systems with interval binary observations, enhancing signal processing techniques.
Using this method, the identification process can adapt dynamically to binary data inputs, leading to more accurate models.
Observational analysis focused on the performance of algorithmic techniques in FIR systems with binary observations.
This work highlights the potential for improved system control, encouraging further exploration in practical applications.

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Implication

This analysis demonstrates recursive identification methods for FIR systems using interval binary observations, implying efficient control algorithms.

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Liu et al. (2026) studied this question.

synapsesocial.com/papers/69a766fcbadf0bb9e87df347 https://doi.org/10.1016/j.ifacsc.2026.100383

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Recursive identification for FIR systems with interval binary observations

Key Points

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Implication

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Recursive identification for FIR systems with interval binary observations

Key Points

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Implication

Discussion

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