Shortest-path recovery from signature with an optimal control approach

Abstract In this paper, we consider the signature-to-path reconstruction problem from the control-theoretic perspective. Namely, we design an optimal control problem whose solution leads to the minimal-length path that generates a given signature. In order to do that, we minimize a cost functional consisting of two competing terms, i.e., a weighted final-time cost combined with the $$L^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>L</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:math> -norm squared of the controls. Moreover, we can show that, by taking the limit to infinity of the parameter that tunes the final-time cost, the problem $$\Gamma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Γ</mml:mi> </mml:math> -converges to the problem of finding a sub-Riemannian geodesic connecting two signatures. Finally, we provide an alternative reformulation of the latter problem, which is particularly suitable for the numerical implementation.

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Publication Details

Journal
Mathematics of Control Signals and Systems
Published
2024-10-14
DOI
https://doi.org/10.1007/s00498-024-00402-8
Citations
1
Primary Topic
Markov Chains and Monte Carlo Methods
Type
article
Field-Weighted Citation Impact
0.71

Funders

Controls
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article

Shortest-path recovery from signature with an optimal control approach

Alessandro Scagliotti, F. Patrı́cio, Marco Rauscher
1 citations
Mathematics of Control Signals and Systems
Markov Chains and Monte Carlo Methods
0.71
article

Shortest-path recovery from signature with an optimal control approach

Alessandro Scagliotti, F. Patrı́cio, Marco Rauscher
article en
1 citations

Abstract

Abstract In this paper, we consider the signature-to-path reconstruction problem from the control-theoretic perspective. Namely, we design an optimal control problem whose solution leads to the minimal-length path that generates a given signature. In order to do that, we minimize a cost functional consisting of two competing terms, i.e., a weighted final-time cost combined with the $$L^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>L</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:math> -norm squared of the controls. Moreover, we can show that, by taking the limit to infinity of the parameter that tunes the final-time cost, the problem $$\Gamma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Γ</mml:mi> </mml:math> -converges to the problem of finding a sub-Riemannian geodesic connecting two signatures. Finally, we provide an alternative reformulation of the latter problem, which is particularly suitable for the numerical implementation.

Mathematics of Control Signals and SystemsVol. 37(2)
Data:Lab Munich (Germany) (DE), Munich Center for Machine Learning, Technical University of Munich (DE)
Istituto Nazionale di Alta Matematica "Francesco Severi", Technische Universität München
Openalex Percentile: Top 26%
Markov Chains and Monte Carlo Methods
0.71
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