786 citations · 2.4k across the 106 of their papers we have counts for
11 papers · 1 filter
System identification of biophysical neuronal models
Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
After sixty years of quantitative biophysical modeling of neurons, the identification of neuronal dynamics from input-output data remains a challenging problem, primarily due to th…
Monotone RLC Circuits
Thomas Chaffey, Rodolphe Sepulchre
The circuit-theoretic origins of maximal monotonicity are revisited using modern optimization algorithms for maximal monotone operators. We present an algorithm for computing the p…
Neuromorphic Control
Luka Ribar, Rodolphe Sepulchre
Neuromorphic engineering is a rapidly developing field that aims to take inspiration from the biological organization of neural systems to develop novel technology for computing, s…
Balanced truncation of -positive systems
Christian Grussler, Tobias Damm, Rodolphe Sepulchre
This paper considers balanced truncation of discrete-time Hankel -positive systems, characterized by Hankel matrices whose minors up to order are nonnegative. Our main resul…
From biophysical to integrate-and-fire modelling
Tomas Van Pottelbergh, Guillaume Drion, Rodolphe Sepulchre
This paper proposes a methodology to extract a low-dimensional integrate-and-fire model from an arbitrarily detailed single-compartment biophysical model. The method aims at relati…
Variation diminishing linear time-invariant systems
Christian Grussler, Rodolphe Sepulchre
This paper studies the variation diminishing property of -positive linear time-invariant (LTI) systems, which map inputs with sign changes to outputs with at most the same…
Inductive Geometric Matrix Midranges
Graham W. Van Goffrier, Cyrus Mostajeran, Rodolphe Sepulchre
Covariance data as represented by symmetric positive definite (SPD) matrices are ubiquitous throughout technical study as efficient descriptors of interdependent systems. Euclidean…
Model reduction by balanced truncation of dominant Lure systems
Alberto Padoan, Fulvio Forni, Rodolphe Sepulchre
The paper presents a model reduction framework geared towards the analysis and design of systems that switch and oscillate. While such phenomena are ubiquitous in nature and engine…
Differential dissipativity analysis of reaction-diffusion systems
Felix Miranda-Villatoro, Rodolphe Sepulchre
This note shows how classical tools from linear control theory can be leveraged to provide a global analysis of nonlinear reaction-diffusion models. The approach is differential in…
Feedback for nonlinear system identification
Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
Motivated by neuronal models from neuroscience, we consider the system identification of simple feedback structures whose behaviors include nonlinear phenomena such as excitability…
Feedback Identification of conductance-based models
Thiago B. Burghi, Maarten Schoukens, Rodolphe Sepulchre
This paper applies the classical prediction error method (PEM) to the estimation of nonlinear discrete-time models of neuronal systems subject to input-additive noise. While the no…