Classes of stochastically switched (blinking) systems

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

The present invention relates to systems and methods for predicting a prognosis of the neuropsychological and/or neuropsychiatric status in a subject based on reports of Minor Hallucination (MH) events in combination with electrophysiological data of the s ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction, and diffusion functions from the path of one single particle in the system. Our estimator is obtained by solving a linear sys ...

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 ...

Self-healing slip pulses are major spatiotemporal failure modes of frictional systems, featuring a characteristic size L(t) and a propagation velocity c(p)(t) (t is time). Here, we develop a theory of slip pulses in realistic rate- and state-dependent fric ...

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 ...

. High-resolution simulations of particle-based kinetic plasma models typically require a high number of particles and thus often become computationally intractable. This is exacerbated in multi-query simulations, where the problem depends on a set of para ...

Systems and methods for monitoring penile tumescence are provided that overcome the drawbacks of previously known systems by providing a wearable formed of a flexible and elastic tube having a plurality of sensors disposed on or embedded within it, the wea ...

We study socio-political systems in representative democracies. Motivated by problems that affect the proper functioning of the system, we build computational methods to answer research questions regarding the phenomena occurring in them. For each phenomen ...

While software applications, programming languages, and hardware have changed, operating systems have not. Widely-used commodity operating systems are still modeled after the ones designed in the seventies. The accumulated burden of backward compatibility ...

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the particle interaction hi ...

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

While systems designers are increasingly turning to hardware accelerators for performance gains, realizing these gains is painstaking and error-prone. It can take several person-months to determine if a given accelerator is a good fit for a given piece of ...

Imaging diagnostics in Joint European Torus have become essential in the study of plasma wall interactions and the protection of the plasma facing components. During deuterium operations, the location of these diagnostics was at close proximity to the vess ...

One approach to understand the chaotic dynamics of nonlinear dissipative systems is the study of non-chaotic yet dynamically unstable invariant solutions embedded in the system's chaotic attractor. The significance of zero-dimensional unstable fixed points ...

Dynamical Systems (DS) are fundamental to the modeling and understanding time evolving phenomena, and have application in physics, biology and control. As determining an analytical description of the dynamics is often difficult, data-driven approaches are ...

Chaotic dynamics in systems ranging from low-dimensional nonlinear differential equations to high-dimensional spatiotemporal systems including fluid turbulence is supported by nonchaotic, exactly recurring time-periodic solutions of the governing equations ...

SEM micrographs of the fracture surface for UO2 ceramic materials have been analysed. In this paper, we introduce some algorithms and develop a computer application based on the time-series method. Utilizing the embedding technique of phase space, the attr ...

Code generation is an effective way to drive the complex system development in model-based systems engineering. Currently, different code generators are developed for different modeling languages to deal with the development of systems with multi-domain. T ...

Classes of stochastically switched (blinking) systems

Chattez avec Graph Search

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

System for predicting a prognosis of the neuropsychological and/or neuropsychiatric status in a subject

Stability: a search for structure

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

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

The dynamics of unsteady frictional slip pulses

Higher-order organization of multivariate time series

Adaptive Symplectic Model Order Reduction Of Parametric Particle-Based Vlasov-Poisson Equation

Tumescense monitoring system for diagnosing erectile dysfunction and methods of use

How Words Move Hearts: Interpretable Machine Learning Models of Bias, Engagement, and Influence in Socio-Political Systems

Dynamic Linkers Are the Narrow Waist of Operating Systems

Learning Physics-Consistent Particle Interactions

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

The Case for Performance Interfaces for Hardware Accelerators

Remote wide angle view broad wavelength viewing system compatible with D-T operations in JET

Invariant tori in dissipative hyperchaos

Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps

Constructing periodic orbits of high-dimensional chaotic systems by an adjoint-based variational method

Spatial Series and Fractal Analysis Associated with Fracture Behaviour of UO2 Ceramic Material

Code Generation Approach Supporting Complex System Modeling based on Graph Pattern Matching