A Fuzzy Clustering Neural Networks (FCNs) system design methodology

Dapeng Zhang, Sankar K. Pal

Research output: Journal article publicationJournal articleAcademic researchpeer-review

17 Citations (Scopus)

Abstract

A system design methodology for fuzzy clustering neural networks (FCNs) is presented. This methodology emphasizes coordination between FCN model definition, architectural description, and systolic implementation. Two mapping strategies both from FCN model to system architecture and from the given architecture to systolic arrays are described. The effectiveness of the methodology is illustrated by: 1) applying the design to an effective FCN model; 2) developing the corresponding parallel architecture with special feedforward and feedback paths; and 3) building the systolic array (SA) suitable for very large scale integration (VLSI) implementation.
Original languageEnglish
Pages (from-to)1174-1177
Number of pages4
JournalIEEE Transactions on Neural Networks
Volume11
Issue number5
DOIs
Publication statusPublished - 1 Dec 2000

Keywords

  • Neuro-fuzzy clustering
  • Systolic array
  • Very large scale integration (VLSI)

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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