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Hybrid multisynchronization of coupled multistable memristive neural networks with time delays
- Source :
- Neurocomputing. 363:281-294
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- In this paper, we focus on synchronization issue of coupled multistable memristive neural networks (CMMNNs) with time delay under multiple stable equilibrium states. First, we build delayed CMMNNs consisting of one master subnetwork without controller and N−1 identical slave subnetworks with controllers, and every subnetwork has n nodes. Moreover, this paper investigates multistability of delayed CMMNNs with continuous nonmonotonic piecewise linear activation function (PLAF) owning 2 r + 2 corner points. By using the theorems of differential inclusion and fixed point, sufficient conditions are derived such that master subnetwork of CMMNNs can acquire ( r + 2 ) n exponentially stable equilibrium points, stable periodic orbits or hybrid stable equilibrium states. Then, this paper proposes hybrid multisynchronization of delayed CMMNNs related with various external inputs under multiple stable equilibrium states for the first time. There exist ( r + 2 ) n hybrid multisynchronization manifolds in CMMNNs with different initial conditions and external inputs. Finally, two numerical simulations are given to illustrate the effectiveness of the obtained results.
- Subjects :
- Equilibrium point
0209 industrial biotechnology
Artificial neural network
Computer science
Cognitive Neuroscience
Activation function
02 engineering and technology
Fixed point
Topology
Synchronization
Computer Science Applications
Piecewise linear function
020901 industrial engineering & automation
Differential inclusion
Exponential stability
Artificial Intelligence
Control theory
0202 electrical engineering, electronic engineering, information engineering
Periodic orbits
020201 artificial intelligence & image processing
Multistability
Subjects
Details
- ISSN :
- 09252312
- Volume :
- 363
- Database :
- OpenAIRE
- Journal :
- Neurocomputing
- Accession number :
- edsair.doi...........2e6039c3d7c4e607b9fd7c145806acef