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Forecasting motion and spatial positions of objects is of fundamental importance, especially in safety-critical settings such as autonomous driving. In this work, we address the issue by forecasting two different modalities that carry…

Computer Vision and Pattern Recognition · Computer Science 2023-11-01 Andrea Ciamarra , Federico Becattini , Lorenzo Seidenari , Alberto Del Bimbo

This paper deals with adaptive synchronization of chaos in the presence of time-varying communication-delays. We consider two bidirectionally coupled systems that seek to synchronize through a signal that each system sends to the other one…

Chaotic Dynamics · Physics 2015-05-30 Francesco Sorrentino , Pietro De Lellis

The prediction of stochastic dynamical systems and the capture of dynamical behaviors are profound problems. In this article, we propose a data-driven framework combining Reservoir Computing and Normalizing Flow to study this issue, which…

Dynamical Systems · Mathematics 2023-08-01 Cheng Fang , Yubin Lu , Ting Gao , Jinqiao Duan

In the present Letter we show that the concept of the generalized synchronization regime in discrete maps needs refining in the same way as it has been done for the flow systems [PRE, 84 (2011) 037201]. We have shown that\alkor{, in the…

By identifying Hamiltonian flows with geodesic flows of suitably chosen Riemannian manifolds, it is possible to explain the origin of chaos in classical Newtonian dynamics and to quantify its strength. There are several possibilities to…

Statistical Mechanics · Physics 2020-01-29 Loris Di Cairano , Matteo Gori , Marco Pettini

When a dynamical system contains several different modes of oscillations it may behave in a variety of ways: If the modes oscillate at their own individual frequencies, it exhibits quasiperiodic behavior; when the modes lock to one another…

Chaotic Dynamics · Physics 2012-01-04 Mogens H. Jensen , Leo P. Kadanoff

We propose and study a system whose dynamics are governed by predictions of its future states. General formalism and concrete examples are presented. We find that the dynamical characteristics depend on both how to shape predictions as well…

Other Condensed Matter · Physics 2007-05-23 Toru Ohira

The scheduling and schedulability analysis of real-time directed acyclic graph (DAG) task systems have received much recent attention. The DAG model can accurately represent intra-task parallelim and precedence constraints existing in many…

Operating Systems · Computer Science 2018-08-02 Zheng Dong , Cong Liu

Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to…

Statistical Mechanics · Physics 2015-07-01 Todd R. Gingrich , Phillip L. Geissler

We introduce a computationally efficient and accurate reduced order modelling approach for the optimization of spatiotemporally chaotic systems. The proposed method combines quantized local reduced order modelling with adjoint-based…

Chaotic Dynamics · Physics 2026-04-10 Defne E. Ozan , Antonio Colanera , Luca Magri

Spatiotemporal chaotic systems are difficult to characterize in a model-free manner because of their high dimensionality, strong nonlinearity, and sensitivity to initial conditions. Coupled map lattices, as a representative class of…

Chaotic Dynamics · Physics 2026-04-15 Xiaoqi Lei , Zixiang Yan , Jian Gao , Yueheng Lan , Jinghua Xiao

A recurrent task in coordinated systems is managing (estimating, predicting, or controlling) signals that vary in space, such as distributed sensed data or computation outcomes. Especially in large-scale settings, the problem can be…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-14 Roberto Casadei , Stefano Mariani , Danilo Pianini , Mirko Viroli , Franco Zambonelli

This chapter offers a principled approach to the prediction of chaotic systems from data. First, we introduce some concepts from dynamical systems' theory and chaos theory. Second, we introduce machine learning approaches for…

Chaotic Dynamics · Physics 2026-04-14 Luca Magri , Andrea Nóvoa , Elise Özalp

We investigate three different methods for systematically approximating the diffusion coefficient of a deterministic random walk on the line which contains dynamical correlations that change irregularly under parameter variation. Capturing…

Mathematical Physics · Physics 2015-05-28 Georgie Knight , Rainer Klages

Living systems exhibit complex yet organized behavior on multiple spatiotemporal scales. To investigate the nature of multiscale coordination in living systems, one needs a meaningful and systematic way to quantify the complex dynamics, a…

Adaptation and Self-Organizing Systems · Physics 2020-03-11 Mengsen Zhang , William D. Kalies , J. A. Scott Kelso , Emmanuelle Tognoli

From the climate system to the effect of the internet on society, chaotic systems appear to have a significant role in our future. Here a method of statistical learning for a class of chaotic systems is described along with underlying…

Applications · Statistics 2020-02-26 Michael LuValle

Continuous adaptation to variable environments is crucial for the survival of living organisms. Here, we analyze how adaptation, forecasting, and resource mobilization towards a target state, termed actionability, interact to determine…

Cell Behavior · Quantitative Biology 2024-04-15 Jose M. G. Vilar , Leonor Saiz

The chaotic synchronization between two bi-directionally coupled external cavity single-mode semiconductor lasers is investigated. Numerical simulation shows that anticipating synchronization and lag synchronization coexist in certain…

Chaotic Dynamics · Physics 2009-11-07 Liang Wu , Shiqun Zhu

In this paper, we compare different map management techniques for long-term visual navigation in changing environments. In this scenario, the navigation system needs to continuously update and refine its feature map in order to adapt to the…

Deducing the states of spatiotemporally chaotic systems (SCSs) as they evolve in time is crucial for various applications. However, it is a dramatic challenge for generally achieving so due to the complexity of non-periodic dynamics and the…

Quantum Physics · Physics 2025-03-04 Longhan Wang , Yifan Sun , Xiangdong Zhang