eagle-i Oregon Health & Science UniversityOregon Health & Science University
See it in Search
This page is a preview of the following resource. Continue onto eagle-i search using the button on the right to see the full record.

Robust Information Filtering Techniques for Static and Dynamic State (State Estimation)

eagle-i ID


Resource Type

  1. Algorithmic software component


  1. Resource Description
    "The software associated with this project aims to improve upon the recent advances in state estimation techniques for nonlinear dynamical systems. These include the unscented Kalman filter, the particle filter, and the sigma-point filters. Previous methods relied heavily on the accurate model knowledge for the specific state estimation domain, whereas many problems involve uncertainty about the dynamic equations and the noise distributions. This software is meant as a robust state estimation algorithms based on information theoretic estimation principles that can handle such uncertainties as well as outliers and sensor failures. These techniques will be used for unobtrusive monitoring of elderly in their homes using motion sensors and RFID transmitters."
  2. Used by
    Center for Spoken Language Understanding
  3. Website(s)
  4. Developed by
    Pavel, Michael, Ph.D.
  5. Software license
    Open source software license
Provenance Metadata About This Resource Record
Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016