A DT-CNN Data-Flow Implementation

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

Digital implementations of Cellular Neural Networks are studied in terms of their communication requirements. Secure and reliable communication seems to imply close control, which degrades performance. We introduce a mechanism that removes the need for explicit local network control, taking the internal network communication out of the performance equation. This allows handling boundary conditions without introducing additional cells and facilitates multi-level implementations. A typical feature extraction task in hand vein recognition shows a 20x performance improvement for the Cellular Neural Network implementation.

Details

Authors
  • Suleyman Malki
  • Lambert Spaanenburg
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Electrical Engineering, Electronic Engineering, Information Engineering
Original languageEnglish
Title of host publication2008 11TH INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS
PublisherIEEE--Institute of Electrical and Electronics Engineers Inc.
Pages17-22
Publication statusPublished - 2008
Publication categoryResearch
Peer-reviewedYes
Event11th International Workshop on Cellular Neural Networks and Their Applications - Santiago de Compostela, SPAIN
Duration: 2008 Jul 142008 Jul 16

Conference

Conference11th International Workshop on Cellular Neural Networks and Their Applications
Period2008/07/142008/07/16