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We provide novel sufficient conditions for stability of nonlinear and time-varying impulsive systems. These conditions generalize, extend, and strengthen many existing results. Different types of input-to-state stability (ISS), as well as…

Systems and Control · Electrical Eng. & Systems 2019-12-11 José L. Mancilla-Aguilar , Hernan Haimovich , Petro Feketa

It has been suggested that adversarial examples cause deep learning models to make incorrect predictions with high confidence. In this work, we take the opposite stance: an overly confident model is more likely to be vulnerable to…

Machine Learning · Computer Science 2018-02-14 Angus Galloway , Graham W. Taylor , Medhat Moussa

In this paper we consider switched nonlinear systems under average dwell time switching signals, with an otherwise arbitrary compact index set and with additional constraints in the switchings. We present invariance principles for these…

Optimization and Control · Mathematics 2009-12-24 J. L. Mancilla-Aguilar , R. A. Garcia

The best developed formulation of closed system quantum theory that handles multiple-time statements, is the consistent (or decoherent) histories approach. The most important weaknesses of the approach is that it gives rise to many…

Quantum Physics · Physics 2014-10-14 Petros Wallden

This paper deals with strong versions of input-to-state stability and integral input-to-state stability of infinite-dimensional linear systems with an unbounded input operator. We show that infinite-time admissibility with respect to inputs…

Functional Analysis · Mathematics 2019-02-05 Robert Nabiullin , Felix Schwenninger

Convolutional and recurrent neural networks have been widely employed to achieve state-of-the-art performance on classification tasks. However, it has also been noted that these networks can be manipulated adversarially with relative ease,…

Machine Learning · Computer Science 2020-09-08 Shankar A. Deka , Dušan M. Stipanović , Claire J. Tomlin

The question of how irreversibility can emerge as a generic phenomena when the underlying mechanical theory is reversible has been a long-standing fundamental problem for both classical and quantum mechanics. We describe a mechanism for the…

Quantum Physics · Physics 2013-09-20 Cozmin Ududec , Nathan Wiebe , Joseph Emerson

Based on the invariance principle of differential equations a simple, systematic, and rigorous feedback scheme with the variable feedback strength is proposed to stabilize nonlinearly any chaotic systems without any prior analytical…

Chaotic Dynamics · Physics 2007-05-23 Debin Huang

Robustness is established for the predictor feedback for linear time-invariant systems with respect to possibly time-varying perturbations of the input delay, with a constant nominal delay. Prior results have addressed qualitatively…

Optimization and Control · Mathematics 2012-07-20 Iasson Karafyllis , Miroslav Krstic

We study the well-posedness and stability of an impedance passive infinite-dimensional linear system under nonlinear feedback of the form $u(t)=\phi(v(t)-y(t))$, where $\phi$ is a monotone function. Our first main result introduces…

Optimization and Control · Mathematics 2025-06-19 Anthony Hastir , Lassi Paunonen

This paper analyzes internal stability of a discrete-time feedback system with a ReLU nonlinearity. This feedback system is motivated by recurrent neural networks. We first review existing static quadratic constraints (QCs) for…

Systems and Control · Electrical Eng. & Systems 2025-11-18 Sahel Vahedi Noori , Bin Hu , Geir Dullerud , Peter Seiler

Negative feedback is a powerful approach capable of improving several aspects of a system. In linear electronics, it has been critical for allowing invariance to device properties. Negative feedback is also known to enhance linearity in…

Instrumentation and Detectors · Physics 2016-11-22 Luciano da F. Costa , Filipi N. Silva , Cesar H. Comin

Counterfactual explanations describe how to modify a feature vector in order to flip the outcome of a trained classifier. Obtaining robust counterfactual explanations is essential to provide valid algorithmic recourse and meaningful…

Machine Learning · Computer Science 2024-03-22 Alexandre Forel , Axel Parmentier , Thibaut Vidal

This note studies the robust output feedback stabilization problem of multi-input multi-output invertible nonlinear systems with output-dependent multipliers. An "ideal" state feedback is first designed under certain mild assumptions. Then,…

Systems and Control · Electrical Eng. & Systems 2021-03-02 Lei Wang , Christopher M. Kellett

This paper studies the feedback stabilization of abstract Cauchy problems with unbounded output operators by finite-dimensional controllers. Both necessary conditions and sufficient conditions for feedback stabilizability are presented. The…

Optimization and Control · Mathematics 2023-09-06 Tian Xia , Giacomo Casadei , Francesco Ferrante , Luca Scardovi

Entropy notions for $\varepsilon$-incremental practical stability and incremental stability of deterministic nonlinear systems under disturbances are introduced. The entropy notions are constructed via a set of points in state space which…

Optimization and Control · Mathematics 2022-09-13 Michelle S. Chong

This paper analyzes the robust feedback stability of a single-input-single-output stable linear time-invariant (LTI) system against four different classes of nonlinear systems using the Zames-Falb multipliers. The contribution is fourfold.…

Systems and Control · Electrical Eng. & Systems 2021-08-19 Sei Zhen Khong , Lanlan Su

We prove a strong non-structure theorem for a class of metric structures with an unstable pair of formulae. As a consequence, we show that weak categoricity (that is, categoricity up to isomorphisms and not isometries) implies several…

Logic · Mathematics 2019-08-20 Saharon Shelah , Alexander Usvyatsov

In this paper, a method is presented to synthesize neural network controllers such that the feedback system of plant and controller is dissipative, certifying performance requirements such as L2 gain bounds. The class of plants considered…

Systems and Control · Electrical Eng. & Systems 2024-04-12 Neelay Junnarkar , Murat Arcak , Peter Seiler

Linear Response theory aims to predict how added forcing alters the statistical properties of an unforced system. These kinds of questions have been studied predominantly for autonomous dynamical systems, yet many systems in the physical,…

Dynamical Systems · Mathematics 2026-04-07 Stefano Galatolo , Valerio Lucarini