Results 241 to 250 of about 6,808,722 (274)

SpectralTCN: A multi-resolution wavelet gating network for vibration-based structural damage detection. [PDF]

PLoS One
Pham Hong Q, Vu Manh T, Nguyen Thach B, Nguyen Dan L, Tran Ngoc H.   +4 more
europepmc   +1 more source

SNR-Weighted Layer-Conditioned Magnetometer Array with Ellipsoid Calibration and Neural Network Initialization for Capsule Endoscopy Localization Under Asymmetric Sensor Visibility. [PDF]

Sensors (Basel)
Yaghoobian O, Wahid KA.
europepmc   +1 more source

Absorption Characteristics of a Passive Damper-Augmented Timoshenko Beam Using a Wave-Decomposition Approach. [PDF]

Sensors (Basel)
Gupta S, Malladi VVNS.
europepmc   +1 more source

Wave propagation in a photo-thermomechanical medium with triple porosity and voids under the Lord-Shulman theory. [PDF]

Sci Rep
Moulahi T, Bouteraa Y, Elidy ES, Sayed HA.   +3 more
europepmc   +1 more source

On the Effect of Quantization on Extended Dynamic Mode Decomposition [PDF]

2025 American Control Conference (ACC)
Extended Dynamic Mode Decomposition (EDMD) is a widely used data-driven algorithm for estimating the Koopman Operator. EDMD extends Dynamic Mode Decomposition (DMD) by lifting the snapshot data using nonlinear dictionary functions before performing the estimation.
Debdipta Goswami, Dipankar Maity
exaly   +5 more sources

Model Predictive Control of Vehicle Dynamics Based on the Koopman Operator With Extended Dynamic Mode Decomposition

2021 22nd IEEE International Conference on Industrial Technology (ICIT), 2021
The control of vehicle dynamics is a very demanding task due to the complex nonlinear tire characteristics and the coupled lateral and longitudinal dynamics of the vehicle. When designing a Model Predictive Controller (MPC) for vehicle dynamics, this can lead to a non- convex optimization problem.
Marko Svec, Jadranko Matusko, Sándor Iles   +2 more
exaly   +5 more sources

Data-Driven MPC With Stability Guarantees Using Extended Dynamic Mode Decomposition [PDF]

IEEE Transactions on Automatic Control
18 pages, 3 ...
Lars Grüne, Manuel Schaller, Lea Bold
exaly   +6 more sources

Extended Dynamic Mode Decomposition With Dictionary Learning Using Neural Ordinary Differential Equations

Nonlinear Theory and Its Applications IEICE, 2021
Nonlinear phenomena can be analyzed via linear techniques using operator-theoretic approaches. Data-driven method called the extended dynamic mode decomposition (EDMD) and its variants, which approximate the Koopman operator associated with the nonlinear phenomena, have been rapidly developing by incorporating machine learning methods.
Sho Shirasaka, Hideyuki Suzuki, Hiroaki Terao   +2 more
exaly   +4 more sources

Group-Convolutional Extended Dynamic Mode Decomposition

Physica D: Nonlinear Phenomena
This paper explores the integration of symmetries into the Koopman-operator framework for the analysis and efficient learning of equivariant dynamical systems using a group-convolutional approach. Approximating the Koopman operator by finite-dimensional surrogates, e.g., via extended dynamic mode decomposition (EDMD), is challenging for high ...
Karl Worthmann, Sebastian Peitz, Feliks Nüske   +2 more
exaly   +4 more sources