Leveraging Arbitrary Mobile Sensor Trajectories With Shallow Recurrent Decoder Networks for Full-State Reconstruction-Reference-Cited by-同舟云学术

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Leveraging Arbitrary Mobile Sensor Trajectories With Shallow Recurrent Decoder Networks for Full-State Reconstruction

Published:2024 Issue: Volume:12 Page:97428-97439
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ebers Megan R.¹^ORCID,Williams Jan P.²,Steele Katherine M.²^ORCID,Nathan Kutz J.³^ORCID

Affiliation:

1. Department of Applied Mathematics, University of Washington, Seattle, WA, USA

2. Department of Mechanical Engineering, University of Washington, Seattle, WA, USA

3. Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA

Funder

U.S. National Science Foundation (NSF) AI Institute for Dynamical Systems

Air Force Office of Scientific Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/6287639/10380310/10584544-aam.pdf

Reference50 articles.

1. Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns

2. The James Webb Space Telescope

3. How advances in neural recording affect data analysis

4. Recurrent neural networks;Medsker;Design Appl.,2001

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