Adaptive Event-Triggered Filtering for Markov Jump Neural Networks Using Quantized Measurement

The problem of extended dissipative filtering is addressed in this paper for Markov jump neural networks that involve both an adaptive event-triggered mechanism and quantization. A mode-dependent filter is designed in this study to ensure that the resulting filtering error system achieves stochastic...

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Auteurs principaux:	Zhewen Sun, Weifeng Xia
Format:	Artigo
Langue:	Inglês
Publié:	IEEE 2026-01-01
Collection:	IEEE Access
Sujets:	Adaptive event-triggered mechanism Markov jump neural networks filter quantization
Accès en ligne:	https://ieeexplore.ieee.org/document/11556146/
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