Initial-induced coexisting and synchronous firing activities in memristor synapse-coupled Morris–Lecar bi-neuron network

Bao, Bocheng; Yang, Qinfeng; Zhu, Dong; Zhang, Yunzhen; Xu, Quan; Chen, Mo

doi:10.1007/s11071-019-05395-7

Cited by 84 publications

(26 citation statements)

References 53 publications

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“…By revising, a resistor in the physical circuit can realize the total amplitude control leaving much margin for chaos application. Like some of the other memristive chaotic systems [48][49][50], the newly proposed chaotic system shows extreme multistability. e implementation of FPGA proves the consistence of theoretical analysis and numerical simulation.…”

Section: Resultsmentioning

confidence: 99%

A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network

Wang

Çiçek

et al. 2021

Complexity

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An amplitude controllable hyperjerk system is constructed for chaos producing by introducing a nonlinear factor of memristor. In this case, the amplitude control is realized from a single coefficient in the memristor. The hyperjerk system has a line of equilibria and also shows extreme multistability indicated by the initial value-associated bifurcation diagram. FPGA-based circuit realization is also given for physical verification. Finally, the proposed memristive hyperjerk system is successfully predicted with artificial neural networks for AI based engineering applications.

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Section: Resultsmentioning

confidence: 99%

A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network

Wang

Çiçek

et al. 2021

Complexity

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“…Particularly, the coexistence of three or more different dynamical states under different initial conditions is called as multistability [31,32]. Multistability means that a rich diversity of stable states exists in a nonlinear system, which reflects the characteristics of the brain itself [33,34]. Numerous electrophysiological experiments show that multistability of firing patterns exist in the electrical activities of biological neurons [35,36].…”

Section: Introductionmentioning

confidence: 99%

Firing multistability in a locally active memristive neuron model

et al. 2020

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The theoretical, numerical and experimental demonstrations of firing dynamics in isolated neuron are of great significance for the understanding of neural function in human brain. In this paper, a new type of locally active and non-volatile memristor with three stable pinched hysteresis loops is presented. Then a novel locally active memristive neuron model is established by using the locally active memristor as a connecting autapse, both firing patterns and multistability in this neuronal system are investigated. We have confirmed that, on the one hand, the construced neuron can generate multiple firing patterns like periodic bursting, periodic spiking, chaotic bursting, chaotic spiking, stochastic bursting, transient chaotic bursting and transient stochastic bursting. On the other hand, the phenomenon of firing multistability with coexisting four kinds of firing patterns can be observed via changing its initial states. It is worth noting that the proposed neuron exhibits such firing multistability previously unobserved in single neuron model. Finally, an electric neuron is designed and implemented, which is extremely useful for the practical scientific and engineering applications. The results captured from neuron hardware experiments match well with the theoretical and numerical simulation results.

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“…e memristor is a novel circuit device with its memductance really depending on the input and with memory effect [20], which is regarded as a valid candidate for neuronal synapse [21]. us, it is interesting to find the emergence of synchronous behavior for memristor synapse-coupled two neurons having different membrane potentials between them [22][23][24][25]. e coexisting firing activities and synchronous behaviors associated to initial condition of the memristor in a memristive synapse-connected Morris-Lecar double neurons' network are explored [22].…”

Section: Introductionmentioning

confidence: 99%

“…us, it is interesting to find the emergence of synchronous behavior for memristor synapse-coupled two neurons having different membrane potentials between them [22][23][24][25]. e coexisting firing activities and synchronous behaviors associated to initial condition of the memristor in a memristive synapse-connected Morris-Lecar double neurons' network are explored [22]. Besides, the coexisting firing activities and initial-associating bifurcation behaviors, as well as the extreme events are disclosed in two adjacent Hindmarsh-Rose neurons connected by flux-controlled memristor [26].…”

Section: Introductionmentioning

confidence: 99%

“…To consider the virtue of FPGA-based realization method, there should be important significance to develop various digital electronic neurons for utilizing in hardware level synthesizers for large-scale neuromprphic circuits. Besides, the digitally circuit-implemented neuron network can effectively imitate the synchronous behavior in the network, which can promote the integrated circuit design and diverse neuron-based engineering applications [22]. To our best knowledge, there is no comprehensive exploration about the Chay neuron model in this valuable approach.…”

Section: Introductionmentioning

confidence: 99%

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Synchronous Behavior for Memristive Synapse-Connected Chay Twin-Neuron Network and Hardware Implementation

Tan

Zhu

et al. 2020

Mathematical Problems in Engineering

Self Cite

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Synchronous behavior can be responsible for the function or dysfunction of a neural network. To employ a memristor with threshold memductance as a bidirectional synapse, a memristive synapse-connected Chay twin-neuron network is constructed. This paper numerically presents the synchronous behavior for four representative firing activities in the memristive twin-neuron network by utilizing time-domain waveforms, synchronized transition states (STSs), and mean synchronization errors (MSEs). Indeed, the synchronous behaviors are truly related to the coupling strength and initial condition of the memristor. Besides, utilizing the powerful XC7Z020 FPGA, a digitally circuit-implemented electro-neuron and the memristive synapse-connected Chay twin-neuron network are made. Thereafter, the four representative firing activities and their STSs are experimentally captured to further confirm the numerical simulations.

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Initial-induced coexisting and synchronous firing activities in memristor synapse-coupled Morris–Lecar bi-neuron network

Cited by 84 publications

References 53 publications

A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network

A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network

Firing multistability in a locally active memristive neuron model

Synchronous Behavior for Memristive Synapse-Connected Chay Twin-Neuron Network and Hardware Implementation

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