Online estimation of biophysical neural networks.
Year: 2021
Type: preprint
Abstract: This paper presents an adaptive observer for online state and parameter estimation of a broad class of biophysical models of neuronal networks. The design closely resembles classical solutions of adaptive control, and the convergence proof is based on contraction analysis. Our results include robustness guarantees with respect to unknown parameter dynamics. We discuss the potential of the approach in neurophysiological applications.
Source: arXiv (Cornell University)
Authors: Thiago B. Burghi, Rodolphe Sepulchre
Institution: University of Cambridge
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3210330089