DocumentCode :
1385030
Title :
A fuzzy clustering neural networks (FCNs) system design methodology
Author :
Zhang, David ; Pal, Sankar K.
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Kowloon, China
Volume :
11
Issue :
5
fYear :
2000
fDate :
9/1/2000 12:00:00 AM
Firstpage :
1174
Lastpage :
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 suitable for VLSI implementation
Keywords :
VLSI; fuzzy neural nets; neural net architecture; systolic arrays; VLSI; architectural description; clustering; fuzzy clustering neural networks; parallel architecture; system design; systolic arrays; Computational modeling; Euclidean distance; Fuzzy neural networks; Fuzzy systems; Joining processes; Neural networks; Neurofeedback; Parallel architectures; Systolic arrays; Very large scale integration;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.870048
Filename :
870048
Link To Document :
بازگشت