Reachable set bounding for delayed memristive neural networks via adaptive control
Abstract
This article is concerned with the reachable set estimation (RSE) for delayed memristive neural networks (MNNs). By exploiting the differential inclusion theory and inequality techniques, the RSE problem of MNNs was investigated. A memoryless adaptive controller was designed to realize that states of MNNs converge to a bounded region. Based on this result, an updated memoryless adaptive controller was designed, which further removed the restriction that the delay derivative must be less than 1, leading to a more general result. The new results were presented in the form of algebraic criteria, which were straightforward to verify. Ultimately, the effectiveness of the proposed criteria was demonstrated through two numerical simulations.
Fields of Study & Subjects
Neural Networks Stability and Synchronization
Advanced Memory and Neural Computing
Neural Networks and Applications
Publication details
- Journal / source
- Networks and Heterogeneous Media
- Publisher
- American Institute of Mathematical Sciences (AIMS)
- Volume
- 21
- Issue
- 1
- Pages
- 198–212
- Publication date
- 1 January 2026