activity
20152021
most citedSingular Dynamic Mode Decompositions

1 citations · 1 across the 2 of their papers we have counts for

collaborators

8 papers

eess.SY20211 cited

Singular Dynamic Mode Decompositions

Joel A. Rosenfeld, Rushikesh Kamalapurkar

This manuscript is aimed at addressing several long standing limitations of dynamic mode decompositions in the application of Koopman analysis. Principle among these limitations ar…

math.OC2021

An occupation kernel approach to optimal control

Rushikesh Kamalapurkar, Joel A. Rosenfeld

In this effort, a novel operator theoretic framework is developed for data-driven solution of optimal control problems. The developed methods focus on the use of trajectories (i.e.…

math.FA2021

Liouville Operators over the Hardy Space

Benjamin P. Russo, Joel A. Rosenfeld

The role of Liouville operators in the study of dynamical systems through the use of occupation measures have been an active area of research in control theory over the past decade…

math.OC2021

Motion Tomography via Occupation Kernels

Benjamin P. Russo, Rushikesh Kamalapurkar, Dongsik Chang +1

The goal of motion tomography is to recover a description of a vector flow field using information on the trajectory of a sensing unit. In this paper, we develop a predictor correc…

math.OC2021

Theoretical Foundations for the Dynamic Mode Decomposition of High Order Dynamical Systems

Joel A. Rosenfeld, Benjamin P. Russo, Rushikesh Kamalapurkar

Conventionally, data driven identification and control problems for higher order dynamical systems are solved by augmenting the system state by the derivatives of the output to for…

math.OC2019

The Gradient descent method from the perspective of fractional calculus

Pham Viet Hai, Joel A. Rosenfeld

Motivated by gradient methods in optimization theory, we give methods based on -fractional derivatives of order in order to solve unconstrained optimization problems. The co…