Nonparametric input estimation in physiological systems: problems, methods, and case studies
Automatica (Journal of IFAC)
Bayesian Function Learning Using MCMC Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Input estimation in nonlinear dynamical systems using differential algebra techniques
Automatica (Journal of IFAC)
Brief Regularization networks for inverse problems: A state-space approach
Automatica (Journal of IFAC)
Regularization networks: fast weight calculation via Kalman filtering
IEEE Transactions on Neural Networks
A Bayesian approach to sparse dynamic network identification
Automatica (Journal of IFAC)
Hi-index | 22.15 |
Many nonlinear optimal control and estimation problems can be formulated as Tikhonov variational problems in an infinite dimensional reproducing kernel Hilbert space. This paper shows that any closed ball contained in such spaces is compact in the sup-norm topology. This result is exploited to obtain conditions which guarantee existence of solutions for the aforementioned problems as well as numerical algorithms whose convergence is guaranteed in the space of continuous functions.