Abstract
In this work we enlarge the class of admissible activation functions, in a Hpfield neural network system, leading to exponential stability. Most of the existing treatments so far consider only Lipschitz continuous activation functions. Here, we discuss the case of functions of “generalized” (L)-type which are not necessarily Lipschitz continuous and systems with variable coefficients. The case of constant coefficients is given as a particular case.
| Original language | English |
|---|---|
| Pages (from-to) | 199-209 |
| Number of pages | 11 |
| Journal | Advanced Mathematical Models and Applications |
| Volume | 4 |
| Issue number | 3 |
| State | Published - 2019 |
Bibliographical note
Publisher Copyright:© 2019, Jomard Publishing. All rights reserved.
Keywords
- (L)-type kernel
- Activation function
- Exponential stabilization
- Neural network
ASJC Scopus subject areas
- Statistics and Probability
- Numerical Analysis
- Modeling and Simulation
- Control and Optimization
- Computational Mathematics
- Applied Mathematics