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A VLSI architecture for fast clustering with fuzzy ART neural networks

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5 Author(s)
E. Granger ; Dept. of Electr. & Comput. Eng., Ecole Polytech. de Montreal, Que., Canada ; Y. Blaquiere ; Y. Savaria ; M. -A. Cantin
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The hardware implementation of the fuzzy ART neural network applied to a demanding real time radar signal clustering problem is investigated. To obtain efficient solutions for implementing this neural network with dedicated hardware, the network's algorithm is reformulated, and then a novel fuzzy ART system architecture is proposed. This system architecture is composed of a global comparator and several identical elementary modules (EMs), each one emulating a number of neurons. The general architecture of each EM consists of a local comparator, dividers, neural processors, and a block of memory

Published in:

Neural Networks for Identification, Control, Robotics, and Signal/Image Processing, 1996. Proceedings., International Workshop on

Date of Conference:

21-23 Aug 1996