1 / 5

Problems in Nonlinear Bayesian Inference

Problems in Nonlinear Bayesian Inference. Dr. Samuel Shapero. Samuel.Shapero@gtri.gatech.edu. June 18 th , 2014. Bayesian Inference. How do we find an optimal hypothesis given available evidence ?. H2. H3. H1. Applications. Multiple Hypothesis Tracking

scout
Download Presentation

Problems in Nonlinear Bayesian Inference

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Problems in NonlinearBayesian Inference Dr. Samuel Shapero Samuel.Shapero@gtri.gatech.edu June 18th, 2014

  2. Bayesian Inference How do we find an optimal hypothesis given available evidence? H2 H3 H1

  3. Applications Multiple Hypothesis Tracking • Target tracking with range-denied measurements (sponsored project) • Agile emitter identification (FY2015 IRAD) Sparse Coding • Subnyquist RWR (FY2015 IRAD) • Compressed Sensing Recovery

  4. N M y â Applications Compressed Sensing Recovery for Medical Imaging [Vasanawala et al. 2011, Shapero et al. 2012] Sparse Components Low Cost Measurement Original Object Compressed Sensing Sparse Approximation x Φ = Recovered Image Bottleneck! Requires speed [Shapero et al., JETCAS, 2012]

  5. Neuromorphic Hardware – RAIN Sparse approximation problems Spiking Neural Networks LOTS OF MATH TESTING CHIP DESIGN RAIN Chip -developed @GT

More Related