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| Title |
Robust Adaptive Synchronization of Ring Configured Uncertain Chaotic FitzHugh–Nagumo Neurons under Direction-Dependent Coupling
|
|---|---|
| Published in |
Frontiers in Neurorobotics, February 2018
|
| DOI | 10.3389/fnbot.2018.00006 |
| Pubmed ID | |
| Authors |
Muhammad Iqbal, Muhammad Rehan, Keum-Shik Hong |
| Abstract |
This paper exploits the dynamical modeling, behavior analysis, and synchronization of a network of four different FitzHugh-Nagumo (FHN) neurons with unknown parameters linked in a ring configuration under direction-dependent coupling. The main purpose is to investigate a robust adaptive control law for the synchronization of uncertain and perturbed neurons, communicating in a medium of bidirectional coupling. The neurons are assumed to be different and interconnected in a ring structure. The strength of the gap junctions is taken to be different for each link in the network, owing to the inter-neuronal coupling medium properties. Robust adaptive control mechanism based on Lyapunov stability analysis is employed and theoretical criteria are derived to realize the synchronization of the network of four FHN neurons in a ring form with unknown parameters under direction-dependent coupling and disturbances. The proposed scheme for synchronization of dissimilar neurons, under external electrical stimuli, coupled in a ring communication topology, having all parameters unknown, and subject to directional coupling medium and perturbations, is addressed for the first time as per our knowledge. To demonstrate the efficacy of the proposed strategy, simulation results are provided. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 27% |
| Student > Ph. D. Student | 2 | 18% |
| Student > Master | 2 | 18% |
| Student > Bachelor | 1 | 9% |
| Unknown | 3 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 36% |
| Agricultural and Biological Sciences | 1 | 9% |
| Mathematics | 1 | 9% |
| Physics and Astronomy | 1 | 9% |
| Psychology | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 3 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 March 2018.
All research outputs
#18,589,103
of 23,025,074 outputs
Outputs from Frontiers in Neurorobotics
#585
of 880 outputs
Outputs of similar age
#256,746
of 330,211 outputs
Outputs of similar age from Frontiers in Neurorobotics
#10
of 17 outputs
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We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.