Search Results for author: Rodolphe Sepulchre

Found 15 papers, 3 papers with code

Graphical Nonlinear System Analysis

no code implementations23 Jul 2021 Thomas Chaffey, Fulvio Forni, Rodolphe Sepulchre

We use the recently introduced concept of a Scaled Relative Graph (SRG) to develop a graphical analysis of input-output properties of feedback systems.

Oscillations in Mixed-Feedback Systems

no code implementations30 Mar 2021 Amritam Das, Thomas Chaffey, Rodolphe Sepulchre

The calculation of the limit cycle is reformulated as the zero finding of a mixed-monotone relation, that is, of the difference of two maximally monotone relations.

Scaled relative graphs for system analysis

no code implementations25 Mar 2021 Thomas Chaffey, Fulvio Forni, Rodolphe Sepulchre

Scaled relative graphs were recently introduced to analyze the convergence of optimization algorithms using two dimensional Euclidean geometry.

Monotone RLC Circuits

no code implementations21 Dec 2020 Thomas Chaffey, Rodolphe Sepulchre

The circuit-theoretic origins of maximal monotonicity are revisited using modern optimization algorithms for maximal monotone operators.

System identification of biophysical neuronal models

no code implementations14 Dec 2020 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 the inherently nonlinear nature of excitable behaviors.

Neuromorphic Control

1 code implementation9 Nov 2020 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, sensing, and actuating.

Inductive Geometric Matrix Midranges

no code implementations2 Jun 2020 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.

Differential dissipativity analysis of reaction-diffusion systems

no code implementations2 May 2020 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.

Feedback Identification of conductance-based models

no code implementations22 Feb 2020 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.

Neuromodulation of Neuromorphic Circuits

1 code implementation15 May 2018 Luka Ribar, Rodolphe Sepulchre

We present a novel methodology to enable control of a neuromorphic circuit in close analogy with the physiological neuromodulation of a single neuron.

Conal Distances Between Rational Spectral Densities

1 code implementation9 Aug 2017 Giacomo Baggio, Augusto Ferrante, Rodolphe Sepulchre

The paper generalizes Thompson and Hilbert metric to the space of spectral densities.

Optimization and Control

Scaled stochastic gradient descent for low-rank matrix completion

no code implementations16 Mar 2016 Bamdev Mishra, Rodolphe Sepulchre

The paper looks at a scaled variant of the stochastic gradient descent algorithm for the matrix completion problem.

Low-Rank Matrix Completion

On the Projective Geometry of Kalman Filter

no code implementations31 Mar 2015 Francesca Paola Carli, Rodolphe Sepulchre

Convergence of the Kalman filter is best analyzed by studying the contraction of the Riccati map in the space of positive definite (covariance) matrices.

Sparse plus low-rank autoregressive identification in neuroimaging time series

no code implementations30 Mar 2015 Raphaël Liégeois, Bamdev Mishra, Mattia Zorzi, Rodolphe Sepulchre

This paper considers the problem of identifying multivariate autoregressive (AR) sparse plus low-rank graphical models.

Time Series

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