Learning the Dynamical System Behind Sensory Data

DOI10.1162/NECO.2010.01-09-941zbMath1198.68195DBLPjournals/neco/LeeL10OpenAlexW2172084389WikidataQ33526432 ScholiaQ33526432MaRDI QIDQ3568381

Soo-Young Lee, Jaehyung Lee

Publication date: 11 June 2010

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco.2010.01-09-941

zbMATH Keywords

delay-embedding theoremdynamical system reconstructionparameter space recovery

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Applications of dynamical systems (37N99) Natural language processing (68T50)

Cites Work

• Delay embeddings for forced systems. I: Deterministic forcing
• Takens embedding theorems for forced and stochastic systems
• Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

This page was built for publication: Learning the Dynamical System Behind Sensory Data