The paper provides the first controllability and observability analysis for structured state-space models, enabling LMI-based controller synthesis via contraction theory and a separation principle for observers and state feedback.
Neu- ral ordinary differential equations,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
xFODE uses incremental states and fuzzy additive models trained with partitioning strategies to deliver accurate yet interpretable nonlinear dynamic models that match NODE and FODE performance on benchmarks.
citing papers explorer
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Controller Design for Structured State-space Models via Contraction Theory
The paper provides the first controllability and observability analysis for structured state-space models, enabling LMI-based controller synthesis via contraction theory and a separation principle for observers and state feedback.
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xFODE: An Explainable Fuzzy Additive ODE Framework for System Identification
xFODE uses incremental states and fuzzy additive models trained with partitioning strategies to deliver accurate yet interpretable nonlinear dynamic models that match NODE and FODE performance on benchmarks.