Reconfigurable Enhanced Spike-Event Neuromorphic Detection of Quasi-DC Signals in Noisy Environments
A technique aimed to work with weak and extremely noisy signals, is presented. The preliminary results of this study indicate that DC or quasi-DC low-intensity light illumination of targets at the presence of strong background noise leads to enhanced Dynamic Vision Detection (DVS) detection, at reduced time resolution. Overall, our technique is aimed at harnessing noise rather eliminating or mitigating it. Exploiting this technique could allow neuromorphic circuits to work with weak and extremely noisy signals, and to develop new detection concepts and applications. The impact of the stochastic resonance on the DC enhanced detection process at the presence of strong amount of noise, is being investigated.
Authors
- Christian Prashad
- Christopher D. Erb (ORCID: https://orcid.org/0000-0002-1649-2324)
- Jack Griffin
- Nicolas Douard (ORCID: https://orcid.org/0000-0002-9999-0125)
- Yi Wang (ORCID: https://orcid.org/0000-0002-6294-1290)
- Gabriel Gojcaj
- George C. Giakos
- Christian Münch
- Frank Maro
- Sofia Bernabei
- Zachary Meryn
- Nicholas Neto
- Kyle Burdick
Institutions
- Bronx High School of Science (US)
- The Bronx Defenders (US)
- Manhattan University (US)
Publication Details
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1109/ist63414.2024.10759167
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00