Inference and control of network dynamics from network structure and geometry
Abstract
The objective of this proposal is to develop a novel algorithm for inferring and mapping the dynamic causal connectivity of information (signaling) flows in networks. To approach the objective, the PI will (1) extend the theoretical construction of a dynamics connectivity framework to accommodate differential signaling speeds along different edges and different internal dynamic models for nodes; (2) incorporate variable signaling and refractory (internal model) dynamics into the PIÕs shortest path recurrence algorithm; (3) analytically predict, i.e. not simulate, observe, and prove recurrent activity and dynamic behavior of a large and complex biological cellular neural network; and (4) prove that the optimized information flow ratio principle represents optimal information flow in networks
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2017
- Source ID
- W911NF1510594
Entities
People
- Gabriel Silva
Organizations
- Army Contracting Command
- United States Army
- University of California, San Diego