3 papers
cs.RO2026
Online sparse Bayesian identification of nonlinear time-varying systems
He Ren, Gaowei Yan, Hang Liu +3
Sparse regression provides a compact and interpretable route for nonlinear system modeling by selecting a small number of active terms from a candidate dictionary. Most sparse regr…
cs.LG2025
Recurrent Stochastic Configuration Networks for Temporal Data Analytics
Dianhui Wang, Gang Dang
Temporal data modelling techniques with neural networks are useful in many domain applications, including time-series forecasting and control engineering. This paper aims at develo…
cs.LG2024
Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling
Gang Dang, Dianhui Wang
Recurrent stochastic configuration networks (RSCNs) have shown great potential in modelling nonlinear dynamic systems with uncertainties. This paper presents an RSCN with hybrid re…