On the implementation of cellular wave computing methods by hardware learning

Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review

Contributors

  • Gunter Geis - , Goethe University Frankfurt a.M. (Author)
  • Frank Gollas - , Goethe University Frankfurt a.M. (Author)
  • Ronald Tetzlaff - , Goethe University Frankfurt a.M. (Author)

Abstract

Adaptive signal processing on Cellular Nonlinear Networks (CNN) based electronic devices is an exciting challenge, which needs a fast and robust parameter adaptation. In this contribution implementations and the analysis of optimisation algorithms will be proposed and discussed using the EyeRIS™hardware system with an embedded ACE16kv2 focal plane processor having 128 × 128 cells. The parameter training performance will be analysed in detail.

Details

Original languageEnglish
Title of host publication2007 IEEE International Symposium on Circuits and Systems (ISCAS)
Pages2930-2933
Number of pages4
Publication statusPublished - 2007
Peer-reviewedYes
Externally publishedYes

Publication series

SeriesProceedings - IEEE International Symposium on Circuits and Systems
ISSN0271-4310

Conference

TitleIEEE International Symposium on Circuits and Systems 2007
Abbreviated titleISCAS 2007
Duration27 - 30 May 2007
Website
CityNew Orleans, LA
CountryUnited States of America

External IDs

ORCID /0000-0001-7436-0103/work/173513961

Keywords

ASJC Scopus subject areas

Keywords

  • Cellular nonlinear networks, EyeRIS visual system, Intelligent sensors, Optimisation algorithm