从具有自交的延时测量中预测动力系统

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-05-03 DOI:10.1016/j.matpur.2024.04.001
Krzysztof Barański , Yonatan Gutman , Adam Śpiewak
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引用次数: 0

摘要

在预测混沌系统行为方面,Schroer、Sauer、Ott 和 Yorke 于 1998 年提出了这样的猜想:如果由黎曼流形 X 的光滑差分变换 T 定义的动力系统具有一个吸引子,其信息维度小于 k 的自然度量 μ,那么对一维观测值 h 的 k 次延时测量一般足以对 h 的未来测量进行 μ 几乎确定的预测。在前一篇论文中,我们在欧几里得空间紧凑集 X 的注入式 Lipschitz 变换 T 与遍历 T 不变的 Borel 概率度量 μ 的条件下建立了这一猜想。在本文中,我们证明了具有任意 Borel 概率度量的紧凑集上所有(也是非可逆的)Lipschitz 系统的猜想,并建立了预测不准确的点集度量的衰减率上限。这部分证实了 Schroer、Sauer、Ott 和 Yorke 提出的第二个猜想,该猜想与经验预测算法以及估算被观测系统的维度和所需延迟测量次数(即所谓的嵌入维度)的算法有关。我们还证明了欧几里得空间中伯乐集上局部利普希兹或荷尔德系统的一般时延预测定理。
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Prediction of dynamical systems from time-delayed measurements with self-intersections

In the context of predicting the behaviour of chaotic systems, Schroer, Sauer, Ott and Yorke conjectured in 1998 that if a dynamical system defined by a smooth diffeomorphism T of a Riemannian manifold X admits an attractor with a natural measure μ of information dimension smaller than k, then k time-delayed measurements of a one-dimensional observable h are generically sufficient for μ-almost sure prediction of future measurements of h. In a previous paper we established this conjecture in the setup of injective Lipschitz transformations T of a compact set X in Euclidean space with an ergodic T-invariant Borel probability measure μ. In this paper we prove the conjecture for all (also non-invertible) Lipschitz systems on compact sets with an arbitrary Borel probability measure, and establish an upper bound for the decay rate of the measure of the set of points where the prediction is subpar. This partially confirms a second conjecture by Schroer, Sauer, Ott and Yorke related to empirical prediction algorithms as well as algorithms estimating the dimension and number of required delayed measurements (the so-called embedding dimension) of an observed system. We also prove general time-delay prediction theorems for locally Lipschitz or Hölder systems on Borel sets in Euclidean space.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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