On adaptive parameters identification of Hindmarsh–Rose neuron models

Aleksandr Kovalchukov and Alexander Fradkov

Chaos, Solitons & Fractals, 2025, vol. 200, issue P1

Abstract: This publication is devoted to the exploration of the Hindmarsh–Rose model, a biological neuron model that provides a good balance between complexity and variability. We focus on the model parameter identification problem, which is a critical aspect of control system theory. The complexity of the problem arises from the presence of numerous nonlinear functions and a large number of unknown parameters. The following sub-issues are covered in this work.

Keywords: Hindmarsh–Rose model; Speed-Gradient algorithm; Biological neural network; Identification problem; Neural dynamics; Adaptive identification; Nonlinear dynamics; Network identification (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:200:y:2025:i:p1:s0960077925008288

DOI: 10.1016/j.chaos.2025.116815

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