Discrete-time Chen Series for Time Discretization and Machine Learning

Discrete-time Chen Series for Time Discretization and Machine Learning
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时间离散化和机器学习的离散时间 Chen 系列

DOI:
10.1109/ciss.2019.8692913
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发表时间:
2019
期刊:
2019 53rd Annual Conference on Information Sciences and Systems (CISS
影响因子:
--
通讯作者:
Espinosa, Luis A.
Espinosa, Luis A.
中科院分区:
--
文献类型:
--
作者:
Gray, W. Steven;Venkatesh, G. S.;Espinosa, Luis A.

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一个以迭代积分为系数的非交换不定式集合上的形式幂级数称为Chen级数,以数学家K. T.尘本文的第一个目标是对Chen级数及其代数结构作一个简要的概述,作为一种参考。第二个目标是详细描述其离散时间模拟,然后将概念应用于两个问题,非线性控制系统的时间离散化问题和动力系统的机器学习问题。
A formal power series over a set of noncommuting indeterminants using iterated integrals as the coefficients is called a Chen series, named after the mathematician K.-T. Chen. The first goal of this paper is to give a brief overview of Chen series and their algebraic structures as a kind of reference point. The second goal is to describe its discrete-time analogue in detail and then apply the concept in two problems, the time discretization problem for nonlinear control systems and the machine learning problem for dynamical systems.
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