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This paper deals with asymptotic stability of a class of dynamical systems in terms of smooth Lyapunov pairs. We point out that well known converse Lyapunov results for differential inclusions cannot be applied to this class of dynamical…

Dynamical Systems · Mathematics 2015-06-30 Michael Schönlein

We say that an algorithm is stable if small changes in the input result in small changes in the output. This kind of algorithm stability is particularly relevant when analyzing and visualizing time-varying data. Stability in general plays…

Data Structures and Algorithms · Computer Science 2025-03-10 Wouter Meulemans , Bettina Speckmann , Kevin Verbeek , Jules Wulms

The search for universal laws that help establish a relationship between dynamics and computation is driven by recent expansionist initiatives in biologically inspired computing. A general setting to understand both such dynamics and…

Machine Learning · Computer Science 2020-09-17 G Manjunath

We introduce a new notion of the stability of computations, which holds under post-processing and adaptive composition. We show that the notion is both necessary and sufficient to ensure generalization in the face of adaptivity, for any…

Machine Learning · Computer Science 2020-01-01 Katrina Ligett , Moshe Shenfeld

In this paper we investigate the stability properties of the so-called gBBKS and GeCo methods, which belong to the class of nonstandard schemes and preserve the positivity as well as all linear invariants of the underlying system of…

Numerical Analysis · Mathematics 2023-04-04 Thomas Izgin , Stefan Kopecz , Angela Martiradonna , Andreas Meister

Linear systems governed by continuous-time difference equations cover a wide class of linear systems. From the Lyapunov-Krasovskii approach, we investigate stability for such a class of systems. Sufficient conditions, and in some particular…

Optimization and Control · Mathematics 2013-12-30 S. Damak , M. Di Loreto , W. Lombardi , V Andrieu

This paper discusses a general and useful stability principle which, roughly speaking, says that given a uniformly continuous function defined on an arbitrary metric space, if the function is bounded on the constraint set and we slightly…

Optimization and Control · Mathematics 2020-09-04 Daniel Reem , Simeon Reich , Alvaro De Pierro

This paper explores the concept of topological transitivity in nonautonomous dynamical systems, which are defined as sequences of continuous maps from a compact metric space to itself. It investigates various conditions (including…

Dynamical Systems · Mathematics 2025-01-22 Michal Málek

The word stable is used to describe a situation when mathematical objects that almost satisfy an equation are close to objects satisfying it exactly. We study operator-algebraic forms of stability for unitary representations of groups and…

Operator Algebras · Mathematics 2025-09-22 Mikael de la Salle

This paper deals with existence and robust stability of hybrid limit cycles for a class of hybrid systems given by the combination of continuous dynamics on a flow set and discrete dynamics on a jump set. For this purpose, the notion of…

Systems and Control · Electrical Eng. & Systems 2023-12-19 Xuyang Lou , Yuchun Li , Ricardo G. Sanfelice

Suppose that two vector fields on a smooth manifold render some equilibrium point globally asymptotically stable (GAS). We show that there exists a homotopy between the corresponding semiflows such that this point remains GAS along this…

Dynamical Systems · Mathematics 2026-01-12 Wouter Jongeneel

This paper focuses on the mathematical approaches to the analysis of stability that is a crucial step in the design of dynamical systems. Three methods are presented, namely, absolutely integrable impulse response, Fourier integral, and…

Systems and Control · Electrical Eng. & Systems 2020-01-06 Kamyar Modjtahedzadeh

We present a new method for learning control law that stabilizes an unknown nonlinear dynamical system at an equilibrium point. We formulate a system identification task in a self-supervised learning setting that jointly learns a controller…

Systems and Control · Electrical Eng. & Systems 2022-03-17 Priyabrata Saha , Magnus Egerstedt , Saibal Mukhopadhyay

A fundamental challenge in learning to control an unknown dynamical system is to reduce model uncertainty by making measurements while maintaining safety. In this work, we formulate a mathematical definition of what it means to safely learn…

Optimization and Control · Mathematics 2020-11-25 Amir Ali Ahmadi , Abraar Chaudhry , Vikas Sindhwani , Stephen Tu

We describe the notion of stability of coherent systems as a framework to deal with redundancy. We define stable coherent systems and show how this notion can help the design of reliable systems. We demonstrate that the reliability of…

We discuss stabilization around trajectories of the continuity equation with nonlocal vector fields, where the control is localized, i.e., it acts on a fixed subset of the configuration space. We first show that the correct definition of…

Optimization and Control · Mathematics 2024-03-06 Nikolay Pogodaev , Francesco Rossi

A commonly used approach to study stability in a complex system is by analyzing the Jacobian matrix at an equilibrium point of a dynamical system. The equilibrium point is stable if all eigenvalues have negative real parts. Here, by…

Populations and Evolution · Quantitative Biology 2016-09-02 James P. L. Tan

A precise meaning is given to the notion of continuous iteration of a mapping. Usual discrete iterations are extended into a dynamical flow which is a homotopy of them all. The continuous iterate reveals that a dynamical map is formend by…

Mathematical Physics · Physics 2009-10-30 R. Aldrovandi , L. P. Freitas

Stability is a general notion that quantifies the sensitivity of a learning algorithm's output to small change in the training dataset (e.g. deletion or replacement of a single training sample). Such conditions have recently been shown to…

Machine Learning · Computer Science 2011-08-18 Stephane Ross , J. Andrew Bagnell

We develop a finite-dimensional sensitivity framework for studying stability in learning systems whose states include representations, parameters, and update variables. The central object is the \emph{Learning Stability Profile}, a…

Machine Learning · Computer Science 2026-05-26 Ronald Katende
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