2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
Login Paper Search My Schedule Paper Index Help

My ICASSP 2021 Schedule

Note: Your custom schedule will not be saved unless you create a new account or login to an existing account.
  1. Create a login based on your email (takes less than one minute)
  2. Perform 'Paper Search'
  3. Select papers that you desire to save in your personalized schedule
  4. Click on 'My Schedule' to see the current list of selected papers
  5. Click on 'Printable Version' to create a separate window suitable for printing (the header and menu will appear, but will not actually print)

Paper Detail

Paper IDSPTM-14.3
Paper Title IMPROVING THE ENERGY-EFFICIENCY OF A KALMAN FILTER USING UNRELIABLE MEMORIES
Authors Jonathan Kern, IMT Atlantique / Polytechnique Montréal, France; Elsa Dupraz, Abdeldjalil Aïssa-El-Bey, IMT Atlantique, France; François Leduc-Primeau, Polytechnique Montréal, Canada
SessionSPTM-14: Models, Methods and Algorithms 2
LocationGather.Town
Session Time:Thursday, 10 June, 13:00 - 13:45
Presentation Time:Thursday, 10 June, 13:00 - 13:45
Presentation Poster
Topic Signal Processing Theory and Methods: [SSP] Statistical Signal Processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Kalman filters are widely used for real-time estimation of dynamic systems, and they sometimes need to be implemented on energy-constrained devices. A Kalman filter implementation from unreliable memories is considered, where the flipping probability of a bit in a memory cell directly depends on its energy consumption. The degradation in estimation performance caused by the noise in the memory is theoretically investigated. Updated equations are then developed for the Kalman filter, taking into account the new source of noise from the unreliable memory. Finally, a method is proposed to optimize the bit energy allocation in the memory, and it is shown from numerical simulations that this method allows for important energy gains.