Abstract
In this paper we show how the stability of a LAPART neural network can be deduced as a result of a general theorem on the input/output stability of nonlinear systems. This result gives conditions on how to choose certain parameters in the LAPART network in order to guarantee stability, which has implications on LAPART's generalization properties and its noise robustness.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1356-1360 |
| Number of pages | 5 |
| Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 2 |
| State | Published - 1997 |
| Externally published | Yes |
| Event | Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - Orlando, FL, USA Duration: Oct 12 1997 → Oct 15 1997 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture