24 citations · 40 across the 8 of their papers we have counts for
8 papers
State Forecasting in an Estimation Framework with Surrogate Sensor Modeling
Sriram Narayanan, Mohamed Naveed Gul Mohamed, Ishan Paranjape +3
In recent years, computational power and data availability breakthroughs have revolutionized our ability to analyze complex physical systems through the inverse problem approach. D…
Parametric Interpolation of Dynamic Mode Decomposition for Predicting Nonlinear Systems
Ananda Chakrabarti, Haitham H. Saleh, Indranil Nayak +3
We present parameter-interpolated dynamic mode decomposition (piDMD), a parametric reduced-order modeling framework that embeds known parameter-affine structure directly into the D…
Temporally-Consistent Bilinearly Recurrent Autoencoders for Control Systems
Ananda Chakrabarti, Indranil Nayak, Debdipta Goswami
This paper introduces the temporally-consistent bilinearly recurrent autoencoder (tcBLRAN), a Koopman operator based neural network architecture for modeling a control-affine nonli…
Time-delayed Dynamic Mode Decomposition for families of periodic trajectories in Cislunar Space
Sriram Narayanan, Mohamed Naveed Gul Mohamed, Indranil Nayak +2
In recent years, the development of the Lunar Gateway and Artemis missions has renewed interest in lunar exploration, including both manned and unmanned missions. This interest nec…
Temporally Consistent Koopman Autoencoders for Forecasting Dynamical Systems
Indranil Nayak, Ananda Chakrabarty, Mrinal Kumar +2
Absence of sufficiently high-quality data often poses a key challenge in data-driven modeling of high-dimensional spatio-temporal dynamical systems. Koopman Autoencoders (KAEs) har…
On the Predictive Capability of Dynamic Mode Decomposition for Nonlinear Periodic Systems with Focus on Orbital Mechanics
Sriram Narayanan, Mohamed Naveed Gul Mohamed, Indranil Nayak +2
This paper discusses the predictive capability of Dynamic Mode Decomposition (DMD) in the context of orbital mechanics. The focus is specifically on the Hankel variant of DMD which…
Accelerating Particle-in-Cell Kinetic Plasma Simulations via Reduced-Order Modeling of Space-Charge Dynamics using Dynamic Mode Decomposition
Indranil Nayak, Fernando L. Teixeira, Dong-Yeop Na +2
We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DM…
Detection and Prediction of Equilibrium States in Kinetic Plasma Simulations via Mode Tracking using Reduced-Order Dynamic Mode Decomposition
Indranil Nayak, Mrinal Kumar, Fernando L. Teixeira
A dynamic mode decomposition (DMD) based reduced-order model (ROM) is developed for tracking, detection, and prediction of kinetic plasma behavior. DMD is applied to the high-fidel…