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STATE ESTIMATION OF MEMRISTOR-BASED STOCHASTIC NEURAL NETWORKS WITH MIXED VARIABLE DELAYS.
- Source :
-
Miskolc Mathematical Notes . 2023, Vol. 24 Issue 3, p1495-1513. 19p. - Publication Year :
- 2023
-
Abstract
- This paper studies the state estimation problem for memristor-based stochastic neural networks (MSNNs) with mixed variable delays. A new Lyapunov-Krasovskii functional (LKF) with quadruple integral terms is incorporated. Then, asymptotic stability conditions are estab- lished for the error system using a linear matrix inequality technique. The estimator gain can be obtained by solving the linear matrix inequalities. Numerical simulations are given to demon- strate the effectiveness and superiority of the new scheme. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MEMRISTORS
*NEURAL circuitry
*LAMMA language
*SEMIGROUPS (Algebra)
*GROUP theory
Subjects
Details
- Language :
- English
- ISSN :
- 17872405
- Volume :
- 24
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Miskolc Mathematical Notes
- Publication Type :
- Academic Journal
- Accession number :
- 174194905
- Full Text :
- https://doi.org/10.18514/MMN.2023.4028