Publications related to Lyapunov exponent

The Strong Integral Input-to-State Stability Property in Dynamical Flow Networks

Dynamical flow networks serve as macroscopic models for, e.g., transportation networks, queuing networks, and distribution networks. While the flow dynamics in such networks follow the conservation of mass on the links, the outflow from each link is often ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Kinetics of information scrambling in correlated metals: Disorder-driven transition from shock wave to Fisher or Kolmogorov-Petrovsky-Piskunov dynamics

Camille Didier Georges Aron

Quenched disorder slows down the scrambling of quantum information. Using a bottom-up approach, we formulate a kinetic theory of scrambling in a correlated metal near a superconducting transition, following the scrambling dynamics as the impurity scatterin ...

Amer Physical Soc2023

Higher-order organization of multivariate time series

Enrico Amico, Andrea Santoro

Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivar ...

NATURE PORTFOLIO2023

Data-driven Methods for Control: from Linear to Lifting

Yingzhao Lian

The progress towards intelligent systems and digitalization relies heavily on the use of automation technology. However, the growing diversity of control objects presents significant challenges for traditional control approaches, as they are highly depende ...

EPFL2023

Study on the possibility of Φ-OTDR sensing in hollow-core fibres

Luc Thévenaz, Malak Mohamed Hossameldeen Omar Mohamed Galal, Yuting Yang

The backscattering process in hollow core fibres shows a large similarity with Rayleigh scattering, offering the potential to be exploited for distributed sensing. A classical Φ-OTDR implementation is used to observe the backscattering signal from the surf ...

SPIE2023

Inception of Regular Valley Spacing in Fluvial Landscapes: A Linear Stability Analysis

Sara Bonetti, Shashank Kumar Anand

Incipient valley formation in mountainous landscapes is often associated with their presence at a regular spacing under diverse hydroclimatic forcings. Here we provide a formal linear stability theory for a landscape evolution model (LEM) representing the ...

2022

Field-dependent roughness of moving domain walls in a Pt/Co/Pt magnetic thin film

Elisabeth Agoritsas

The creep motion of domain walls driven by external fields in magnetic thin films is described by universal features related to the underlying depinning transition. One key parameter in this description is the roughness exponent characterizing the growth o ...

2021

Feedback Control Design Maximizing the Region of Attraction of Stochastic Systems Using Polynomial Chaos Expansion

Petr Listov

A feedback control design is proposed for stochastic systems with finite second moment which aims at maximising the region of attraction of the equilibrium point. Polynomial Chaos (PC) expansions are employed to represent the stochastic closed loop system ...

ELSEVIER2020

Low-Rank Updates And A Divide-And-Conquer Method For Linear Matrix Equations

Daniel Kressner, Stefano Massei

Linear matrix equations, such as the Sylvester and Lyapunov equations, play an important role in various applications, including the stability analysis and dimensionality reduction of linear dynamical control systems and the solution of partial differentia ...

SIAM PUBLICATIONS2019

Compressive sensing adaptation for polynomial chaos expansions

Panagiotis Tsilifis

Basis adaptation in Homogeneous Chaos spaces rely on a suitable rotation of the underlying Gaussian germ. Several rotations have been proposed in the literature resulting in adaptations with different convergence properties. In this paper we present a new ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2019

Nonlinear dynamic analysis of D-alpha signals for type I edge localized modes characterization on JET with a carbon wall

Olivier Sauter, Ambrogio Fasoli, Basil Duval, Stefano Coda, Martinus Gijs, Jonathan Graves, Yves Martin, Duccio Testa, Patrick Blanchard, Joan Decker, Cristian Galperti, Bruno Emanuel Ferreira De Sousa Correia, Pierre-Thomas Paul Brun, Daniel Filipe Dos Santos Alves Jana, Henri Weisen, Richard Pitts, Javier García Hernández, Sun Hee Kim, Jan Horacek, Marco Wischmeier, Federico Nespoli, Mikhail Maslov, David Pfefferlé, Miguel Fernández Ruiz, Jonathan Marc Philippe Faustin, Antonio José Pereira de Figueiredo, Liang Yao, Dalziel Joseph Wilson, Robin Humphry-Baker, José Pedro Rebelo Ferreira Marques, Andrea Scarabosio, Gilles Arnoux, Jonnathan Cesar Hidalgo Acosta, Pedro Camilo de Oliveira e Silva, Bernhard Sieglin, Thomas Jean F Bauwens, Vlad Trifa, Otto Asunta, Rebecca Hill,

Solving Rank-Structured Sylvester And Lyapunov Equations

Stefano Massei

We consider the problem of efficiently solving Sylvester and Lyapunov equations of medium and large scale, in case of rank-structured data, i.e., when the coefficient matrices and the right-hand side have low-rank off-diagonal blocks. This comprises proble ...

SIAM PUBLICATIONS2018

Compliant control of Uni/ Multi- robotic arms with dynamical systems

Seyed Sina Mirrazavi Salehian

Accomplishment of many interactive tasks hinges on the compliance of humans. Humans demonstrate an impressive capability of complying their behavior and more particularly their motions with the environment in everyday life. In humans, compliance emerges fr ...

EPFL2018

Deriving fragility functions from bilinearized capacity curves for earthquake scenario modelling using the conditional spectrum

Pierino Lestuzzi, Clotaire Michel, Pia Hannewald

The development of fragility curves to perform seismic scenario-based risk assessment requires a fully probabilistic procedure in order to account for uncertainties at each step of the computation. This is especially true when developing fragility curves c ...

SPRINGER2018

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

Wulfram Gerstner, Aditya Gilra

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedfo ...

Elife Sciences Publications Ltd2017

Geometric phases in discrete dynamical systems

Nicolas Piro Mastracchio

In order to study the behaviour of discrete dynamical systems under adiabatic cyclic variations of their parameters, we consider discrete versions of adiabatically-rotated rotators. Parallelling the studies in continuous systems, we generalize the concept ...

Elsevier Science Bv2016

Lyapunov Exponents for Branching Processes in a Random Environment: The Effect of Information

Sophie Myriam Hautphenne

We consider multitype branching processes evolving in a Markovian random environment. To determine whether or not the branching process becomes extinct almost surely is akin to computing the maximal Lyapunov exponent of a sequence of random matrices, which ...

Springer Verlag2016

The U (n) free rigid body: Integrability and stability analysis of the equilibria

Tudor Ratiu

A natural extension of the free rigid body dynamics to the unitary group U (n) is considered. The dynamics is described by the Euler equation on the Lie algebra u(n), which has a bi-Hamiltonian structure, and it can be reduced onto the adjoint orbits, as i ...

Elsevier2015

Learning control Lyapunov function to ensure stability of dynamical system-based robot reaching motions

Aude Billard, Seyed Mohammad Khansari Zadeh

We consider an imitation learning approach to model robot point-to-point (also known as discrete or reaching) movements with a set of autonomous Dynamical Systems (DS). Each DS model codes a behavior (such as reaching for a cup and swinging a golf club) at ...

Elsevier2014

Coupling Movement Primitives: Interaction With the Environment and Bimanual Tasks

Auke Ijspeert

The framework of dynamic movement primitives (DMPs) contains many favorable properties for the execution of robotic trajectories, such as indirect dependence on time, response to perturbations, and the ability to easily modulate the given trajectories, but ...

Ieee-Inst Electrical Electronics Engineers Inc2014