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Dynamics, synchronization and analog circuit implementation of a discrete neuron-like map with pulsating spiral dynamics

Wanting Zhu, Kehui Sun, Huihai Wang, Longxiang Fu and Ludovico Minati

Chaos, Solitons & Fractals, 2024, vol. 186, issue C

Abstract: Owing to their computational efficiency and generative potential, discrete neural models have been gaining interest, both theoretically and towards engineering applications. In this paper, we propose a discrete map endowed with neuron-like dynamics and two distinguishing properties. Namely, the attractor has a spiral topology, and it has a cavity. The size of this cavity shows a non-monotonic relationship to a control parameter, delineating a pulsating behavior. The map shows a multitude of qualitatively-different periodic, chaotic, and hyperchaotic behaviors as a function of the control parameter settings, and its jump points restrict the internal and external size of the attractor. The oscillation frequency is also controllable and also shows a non-monotonic effect. In preparation for future work realizing neural-like networks, we demonstrate the synchronizability by coupling two nodes through a quadratic discrete memristor as the synapse. Finally, the analog circuit realizing this map is implemented and its dynamics are studied experimentally via a comprehensive set of measurements. As the control parameter is varied, the dynamic contraction and expansion of the attractor are observed alongside its well-developed spiral structure.

Keywords: Analog electronic circuit; Discrete dynamics; Memristive synapse; Neural model; Pulsating attractor; Spiral; Synchronization (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:186:y:2024:i:c:s0960077924008336

DOI: 10.1016/j.chaos.2024.115281

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