Statistical Theories of Inference for Coherent Signals

Research supported in part by AFOSR DDDAS Program, Lincoln Laboratory, MISTI, NSF, and NUWC

AROMA: Adaptive Reduced Order Modeling by Alignment for Coherent Fluids

Sun, 09/01/2013

A new Offline-Online scheme for dealing with coherent fluids in Dynanmic Data-Driven Application Systems. 

For coherent fluids, Empirical Orthogonal Functions (EOF) or Proper Orthogonal Decomposition (POD) fail in the presence of deformations (or feature displacements). We propose a joint amplitude-deformation approach to solve this problem and the paper can be found here. Please watch this space for examples)!