The National Science Foundation (NSF) awarded a $175,000 project grant under the Mathematical and Physical Sciences (CFDA 47.049) program to Embry-Riddle Aeronautical University, Inc. The grant, effective August 1, 2024 through July 31, 2027, will support collaborative research to develop data-driven methods for realizing and predicting the behavior of state-space dynamical systems using low-complexity algorithms.
The project aims to leverage advanced machine learning techniques to efficiently analyze and predict information within high-dimensional data matrices and tensor computations for state-space systems. Key objectives include utilizing machine learning to forecast future states of dynamical systems, realizing controllable and observable state-space systems through low-complexity algorithms, analyzing system noise and resilience, and optimizing applications such as spacecraft trajectory planning. This research is expected to advance the understanding of complex, chaotic dynamical systems and support STEM education and workforce development.
Generated 3/18/25, 4:53 AM