Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/214
Title: A fuzzy clustering neural networks (FCNs) system design methodology
Authors: Zhang, David D.
Pal, Sankar K.
Subjects: Neuro-fuzzy clustering
Systolic array
Very large scale integration (VLSI)
Issue Date: Sep-2000
Publisher: IEEE
Source: IEEE transactions on neural networks, Sept. 2000, v. 11, no. 5, p.1174-1177.
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.
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Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/214
DOI: 10.1109/72.870048
ISSN: 1045-9227
Appears in Collections:COMP Journal/Magazine Articles

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