Helping Communicate Research Ideas to the Broader Community

Stacks Image 1934

Data-driven sensor placement methods

 

This video highlights highlights data-driven methods and dimensionality reduction for optimal sensor placement.
[View]

 

 

 

Stacks Image 27909

Sparse identification of insect wing strain

 

This video highlights methods for exploiting sparsity on insect wing strain signals for downstream environmental identification.
[View]

 

 

 

Stacks Image 27840

Data-driven discovery of partial differential equations

 

This video highlights extensions of our sparse identification for nonlinear dynamical systems (SINDy) to partial differential equations.
[View]

 

 

 

Stacks Image 21188

Data-driven methods for discovery of observables and Koopman embeddings in dynamical systems

 

This video highlights a presentation at the IPAM workshop on Collective Variables in Classical Mechanics (Workshop II from October 24-28, 2016).
[View]

 

  • Primary collaborators Steven Brunton and Joshua Proctor

 

 

Stacks Image 16178

Hankel Alternative View of Koopman (HAVOK) Analysis

 

This video highlights a new algorithm to decompose chaos into a linear system with intermitting forcing.
[View]

 

 

 

Stacks Image 16133

Sparse Sensor Placement Optimization for Classification (SSPOC)

 

This video highlights the new innovations around using sparsity promoting techniques for determining optimal sensor placement.
[View]

 

 

 

Stacks Image 15178

Generalizing Koopman Theory to Allow for Inputs and Control

 

This video highlights the new innovations around Koopman theory and data-driven control strategies.
[View]

 

 

 

Stacks Image 11012

Dynamic Mode Decomposition with Control

 

This video highlights the concepts of Dynamic Mode Decomposition which includes actuation and control.
[View]

 

 

 

Stacks Image 11372

Inferring biological networks by sparse idendification of nonlinear dynamics

 

This video highlights the concepts of sparse regression for identifying nonlinear dynamical systems that are of the form dy/dt=f(y)/g(y) which often arise in biological networks.
[View]

 

 

 

Stacks Image 10955

Koopman theory for partial differential equations

 

This video highlights the concepts of Koopman theory and how they can be used for partial differential equations.
[View]

 

 

 

Stacks Image 10633

Online interpolation point refinement for reduced order models using a genetic algorithm

 

This video highlights the use of a genetic algorithm for optimizing interpolation approximations in nonlinear model reduction.
[View]

 

 

 

Stacks Image 10576

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

 

This video highlights the recent innovation of using overcomplete libraries and sparse regression to discover nonlinear dynamical systems from time series data.
[View]

 

 

 

Stacks Image 9099

Koopman observable subspaces and finite linear representations of nonlinear dynamical systems for control

 

This video highlights the recent innovation of Koopman analysis for representing nonlinear systems and control.
[Part 1], [Part 2], [Part 3]

 

 

 

Stacks Image 8851

Nonlinear Model Reduction for Dynamical Systems using Sparse Optimal Sensor Locations from Learned Nonlinear Libraries

 

This video highlights the recent innovation of library learning architecture with the DEIMS method on reduced order models.
[View]

 

 

 

Stacks Image 7359

Multi-Resolution Dynamic Mode Decomposition

 

This video highlights the recent innovation of multi-resolution analysis applied to dynamic mode decomposition.
[View]

 

 

 

Stacks Image 7436

What is a Koopman Mode?

 

This video highlights how one might define a Koopman Mode.
[View]

 

  • Arxiv paper: There is no research article available at the current time
© 2015 kutz Contact Me