IDENTIFICATION OF RELIABLE PREDICTOR MODELS FOR UNKNOWN SYSTEMS: A DATA-CONSISTENCY APPROACH BASED ON LEARNING THEORY
- 1 January 2002
- journal article
- Published by Elsevier in IFAC Proceedings Volumes
- Vol. 35 (1) , 85-90
- https://doi.org/10.3182/20020721-6-es-1901.01000
Abstract
No abstract availableKeywords
This publication has 7 references indexed in Scilit:
- Finite sample properties of system identification of ARX models under mixing conditionsAutomatica, 2000
- Learning dynamical systems in a stationary environmentSystems & Control Letters, 1998
- Polynomial Bounds for VC Dimension of Sigmoidal and General Pfaffian Neural NetworksJournal of Computer and System Sciences, 1997
- Semidefinite ProgrammingSIAM Review, 1996
- Rates of Convergence for Empirical Processes of Stationary Mixing SequencesThe Annals of Probability, 1994
- A note on uniform laws of averages for dependent processesStatistics & Probability Letters, 1993
- On the Uniform Convergence of Relative Frequencies of Events to Their ProbabilitiesTheory of Probability and Its Applications, 1971