A Jordan recurrent network estimator is shown to have input-to-state stable error dynamics, with stability certified by SMT-verified Lyapunov functions and demonstrated on three example systems.
The new trend of state estimation: from model-driven to hybrid-driven methods,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
math.OC 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
Stability of Jordan Recurrent Neural Network Estimator
A Jordan recurrent network estimator is shown to have input-to-state stable error dynamics, with stability certified by SMT-verified Lyapunov functions and demonstrated on three example systems.