SUMMARY

This work explores the usage of the Information Theory Metric of Causation Entropy as a preprocessing technique to explore the sparcity of a proposed model to reduce the order of the required optimization problem for improved performance. The work explores its capabilities through simulation to develop the potential uses in an ideal setting. The work then explores some of the practical considerations for using the technique including the effects of noise on the system as well as sampling rate considerations. Finally, the work will explore an example on a real, physical system.