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Abstract:
This paper presents a novel and fast k-NN classifier that is
based on a binary CMM (Correlation Matrix Memory) neural network. A
robust encoding method is developed that converts numerical inputs
into binary ones to meet CMM input requirements. A hardware
implementation of the CMM is described, which gives over 200 times
the speed of a current mid-range workstation, and is scaleable to
very large problems. When tested on several benchmarks and compared
with a simple k-NN method, the CMM classifier gave less than 1
lower accuracy and over 4 and 12 times speed-ups in software and
hardware respectively.
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