Port-Hamiltonian Dynamic Mode Decomposition (Q6116390)

scientific article; zbMATH DE number 7713604

Language	Label	Description	Also known as
English	Port-Hamiltonian Dynamic Mode Decomposition	scientific article; zbMATH DE number 7713604

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instance of

scholarly article

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title

Port-Hamiltonian Dynamic Mode Decomposition (English)

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SIAM Journal on Scientific Computing

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publication date

18 July 2023

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full work available at URL

https://arxiv.org/abs/2204.13474

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zbMATH Keywords

dynamic mode decomposition

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port-Hamiltonian systems

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system identification

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dissipation inequality

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passivity

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knowledge-driven realization

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MaRDI profile type

MaRDI publication profile

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cites work

Port-Hamiltonian formulations of poroelastic network models

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Model Reduction and Approximation

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Robust port-Hamiltonian representations of passive systems

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Linear port-Hamiltonian descriptor systems

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Operator inference and physics-informed learning of low-dimensional models for incompressible flows

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Identification of port-Hamiltonian systems from frequency response data

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On reduced input-output dynamic mode decomposition

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Extended Balancing of Continuous LTI Systems: A Structure-Preserving Approach

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Error bounds for port-Hamiltonian model and controller reduction based on system balancing

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Passivity preserving model reduction via spectral factorization

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Least Squares Solution of BXAT=T over Symmetric, Skew-Symmetric, and Positive Semidefinite X

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On computing the distance to stability for matrices using linear dissipative Hamiltonian systems

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A semi-analytical approach for the positive semidefinite Procrustes problem

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Structure-preserving tangential interpolation for model reduction of port-Hamiltonian systems

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Q4730687

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Linear port-Hamiltonian systems on infinite-dimensional spaces.

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An eigensystem realization algorithm for modal parameter identification and model reduction

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Dynamic Mode Decomposition with Control

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A framework for the solution of the generalized realization problem

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Introductory lectures on convex optimization. A basic course.

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Data-Driven Reduced Model Construction with Time-Domain Loewner Models

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Data-driven operator inference for nonintrusive projection-based model reduction

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Structure Preserving Moment Matching for Port-Hamiltonian Systems: Arnoldi and Lanczos

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Effort- and flow-constraint reduction methods for structure preserving model reduction of port-Hamiltonian systems

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Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

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Structure-Preserving $H^2$ Optimal Model Reduction Based on the Riemannian Trust-Region Method

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Dynamic mode decomposition of numerical and experimental data

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Data-driven interpolation of dynamical systems with delay

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Data-driven structured realization

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SOBMOR: Structured Optimization-Based Model Order Reduction

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Hamiltonian operator inference: physics-preserving learning of reduced-order models for canonical Hamiltonian systems

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On dynamic mode decomposition: theory and applications

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Port-Hamiltonian Systems Theory: An Introductory Overview

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Passivity and structure preserving order reduction of linear port-Hamiltonian systems using Krylov subspaces

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Mathematics(1 entry)

mardi Publication:6116390