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- Title
Lag Synchronization of Noisy and Nonnoisy Multiple Neurobiological Coupled FitzHugh–Nagumo Networks with and without Delayed Coupling.
- Authors
Ibrahim, Malik Muhammad; Iram, Shazia; Kamran, Muhammad Ahmad; Naeem Mannan, Malik Muhammad; Ali, Muhammad Umair; Jung, Il Hyo; Kim, Sangil
- Abstract
This paper presents a methodology for synchronizing noisy and nonnoisy multiple coupled neurobiological FitzHugh–Nagumo (FHN) drive and slave neural networks with and without delayed coupling, under external electrical stimulation (EES), external disturbance, and variable parameters for each state of both FHN networks. Each network of neurons was configured by considering all aspects of real neurons communications in the brain, i.e., synapse and gap junctions. Novel adaptive control laws were developed and proposed that guarantee the synchronization of FHN neural networks in different configurations. The Lyapunov stability theory was utilized to analytically derive the sufficient conditions that ensure the synchronization of the FHN networks. The effectiveness and robustness of the proposed control laws were shown through different numerical simulations.
- Subjects
NEURAL circuitry; SYNCHRONIZATION; ELECTRIC stimulation; LYAPUNOV stability; ADAPTIVE control systems; STABILITY theory
- Publication
Computational Intelligence & Neuroscience, 2022, p1
- ISSN
1687-5265
- Publication type
Article
- DOI
10.1155/2022/5644875