Abstract
This paper addresses the problem of estimating training error bounds of state and output trajectories for a class of recurrent neural networks as models of nonlinear dynamic systems. The bounds are obtained provided that the models have been trained on N trajectories with N independent random initial values which are uniformly distributed over [a, b] m ∈R m.
Original language | English (US) |
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Title of host publication | Proceedings of the IEEE Conference on Decision and Control |
Publisher | IEEE |
Pages | 1574-1578 |
Number of pages | 5 |
Volume | 2 |
State | Published - 1997 |
Event | Proceedings of the 1997 36th IEEE Conference on Decision and Control. Part 1 (of 5) - San Diego, CA, USA Duration: Dec 10 1997 → Dec 12 1997 |
Other
Other | Proceedings of the 1997 36th IEEE Conference on Decision and Control. Part 1 (of 5) |
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City | San Diego, CA, USA |
Period | 12/10/97 → 12/12/97 |
ASJC Scopus subject areas
- Chemical Health and Safety
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality