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This work describes and analyzes the domain derivative for a time-dependent acoustic scattering problem. We study the nonlinear operator that maps a sound-soft scattering object to the solution of the time-dependent wave equation evaluated…

Numerical Analysis · Mathematics 2025-10-27 Marvin Knöller , Jörg Nick

In this paper we provide a complete link between dissipation theory and a celebrated result on stability analysis with integral quadratic constraints. This is achieved with a new stability characterization for feedback interconnections…

Optimization and Control · Mathematics 2018-03-16 Carsten W. Scherer , Joost Veenman

Existing frequency domain methods for bootstrapping time series have a limited range. Consider for instance the class of spectral mean statistics (also called integrated periodograms) which includes many important statistics in time series…

Methodology · Statistics 2018-06-19 Marco Meyer , Efstathios Paparoditis , Jens-Peter Kreiss

Dynamic mode decomposition (DMD) provides a principled approach to extract physically interpretable spatial modes from time-resolved flow field data, along with a linear model for how the amplitudes of these modes evolve in time. Recently,…

Fluid Dynamics · Physics 2020-07-29 Aditya G. Nair , Benjamin Strom , Bingni W. Brunton , Steven L. Brunton

This paper is concerned with the study of the stability of dynamical systems evolving on time scales. We first {formalize the notion of matrix measures on time scales, prove some of their key properties and make use of this notion to study…

Dynamical Systems · Mathematics 2022-06-10 Giovanni Russo , Fabian Wirth

Recently, frequency transformation (FT) has been increasingly incorporated into deep learning models to significantly enhance state-of-the-art accuracy and efficiency in time series analysis. The advantages of FT, such as high efficiency…

Machine Learning · Computer Science 2025-06-16 Kun Yi , Qi Zhang , Wei Fan , Longbing Cao , Shoujin Wang , Guodong Long , Liang Hu , Hui He , Qingsong Wen , Hui Xiong

In 1980 and 1981, two pioneering papers laid the foundation for what became known as nonlinear time-series analysis: the analysis of observed data---typically univariate---via dynamical systems theory. Based on the concept of state-space…

Chaotic Dynamics · Physics 2015-06-24 Elizabeth Bradley , Holger Kantz

We investigate two classes of quantum control problems by using frequency-domain optimization algorithms in the context of ultrafast laser control of quantum systems. In the first class, the system model is known and a frequency-domain…

Quantum Physics · Physics 2022-01-19 Daoyi Dong , Chuan-Cun Shu , Jiangchao Chen , Xi Xing , Hailan Ma , Yu Guo , Herschel Rabitz

Nonlinear optical frequency conversion, observed more than half a century ago, is a corner stone in modern applications of nonlinear and quantum optics. It is well known that frequency conversion processes are constrained by conservation…

Optics · Physics 2022-11-23 Stefano Longhi

A key factor that generates significant interest in reset control systems, especially within industrial contexts, is their potential to be designed using a frequency-domain loop-shaping procedure. On the other hand, formulating and…

Systems and Control · Electrical Eng. & Systems 2025-02-14 S. Ali Hosseini , S. Hassan HosseinNia

Deep learning-based methods deliver state-of-the-art performance for solving inverse problems that arise in computational imaging. These methods can be broadly divided into two groups: (1) learn a network to map measurements to the signal…

Image and Video Processing · Electrical Eng. & Systems 2023-10-11 Nebiyou Yismaw , Ulugbek S. Kamilov , M. Salman Asif

We present a theoretical method to generate a highly accurate {\em time-independent} Hamiltonian governing the finite-time behavior of a time-periodic system. The method exploits infinitesimal unitary transformation steps, from which…

Statistical Mechanics · Physics 2019-05-30 Michael Vogl , Pontus Laurell , Aaron D. Barr , Gregory A. Fiete

Flying animals possess highly complex physical characteristics and are capable of performing agile maneuvers using their wings. The flapping wings generate complex wake structures that influence the aerodynamic forces, which can be…

Robotics · Computer Science 2022-07-26 Eric Sihite , Paul Ghanem , Adarsh Salagame , Alireza Ramezani

We develop quantum electrodynamics into a kinetic-theory-like evolution equation for electrons, positrons and photons. To keep the "collision rules" simple, we make use of longitudinal and temporal photons in addition to the usual…

High Energy Physics - Theory · Physics 2018-03-09 Hans Christian Öttinger

Time series forecasting is essential in a wide range of real world applications. Recently, frequency-domain methods have attracted increasing interest for their ability to capture global dependencies. However, when applied to non-stationary…

Machine Learning · Statistics 2026-02-09 Zhongde An , Jinhong You , Jiyanglin Li , Yiming Tang , Wen Li , Heming Du , Shouguo Du

Phase difference function is established by means of phase transfer function between time domains of source and interference point. The function reveals a necessary interrelation between outcome of two-beam interference, source's frequency…

Optics · Physics 2007-05-23 Ji Luo

The Carleman linearization is one of the mainstream approaches to lift a finite-dimensional nonlinear dynamical system into an infinite-dimensional linear system with the promise of providing accurate approximations of the original…

Dynamical Systems · Mathematics 2022-07-21 Arash Amini , Cong Zheng , Qiyu Sun , Nader Motee

A nonlinear frequency response based adaptive vibration controller is proposed for a class of nonlinear mechanical systems. In order to obtain the nonlinear Frequency Response Function (FRF), the convergence properties of the system are…

Systems and Control · Computer Science 2015-03-30 Suresh Thenozhi , Yu Tang

Machine learning traditionally assumes that the training and testing data are distributed independently and identically. However, in many real-world settings, the data distribution can shift over time, leading to poor generalization of…

Machine Learning · Computer Science 2024-02-19 Sepidehsadat Hosseini , Mengyao Zhai , Hossein Hajimirsadegh , Frederick Tung

Time-frequency transforms represent a signal as a mixture of its time domain representation and its frequency domain representation. We present efficient algorithms for the quantum Zak transform and quantum Weyl-Heisenberg transform.

Quantum Physics · Physics 2007-05-23 J. Mark Ettinger