TY - GEN
T1 - Algorithmic (Semi-)Conjugacy via Koopman Operator Theory
AU - Redman, William T.
AU - Fonoberova, Maria
AU - Mohr, Ryan
AU - Kevrekidis, Ioannis G.
AU - Mezic, Igor
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Iterative algorithms are of utmost importance in decision and control. With an ever growing number of algorithms being developed, distributed, and proprietarized, there is a similarly growing need for methods that can provide classification and comparison. By viewing iterative algorithms as discrete-time dynamical systems, we leverage Koopman operator theory to identify (semi-)conjugacies between algorithms using their spectral properties. This provides a general framework with which to classify and compare algorithms.
AB - Iterative algorithms are of utmost importance in decision and control. With an ever growing number of algorithms being developed, distributed, and proprietarized, there is a similarly growing need for methods that can provide classification and comparison. By viewing iterative algorithms as discrete-time dynamical systems, we leverage Koopman operator theory to identify (semi-)conjugacies between algorithms using their spectral properties. This provides a general framework with which to classify and compare algorithms.
UR - https://www.scopus.com/pages/publications/85147005359
UR - https://www.scopus.com/pages/publications/85147005359#tab=citedBy
U2 - 10.1109/CDC51059.2022.9992592
DO - 10.1109/CDC51059.2022.9992592
M3 - Conference contribution
AN - SCOPUS:85147005359
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 6006
EP - 6011
BT - 2022 IEEE 61st Conference on Decision and Control, CDC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 61st IEEE Conference on Decision and Control, CDC 2022
Y2 - 6 December 2022 through 9 December 2022
ER -