Abstract
This paper describes research into the hardware implementation of a binary correlation matrix memory (CMM) neural network. It shows that the network can be implemented with on-board training and testing that operates at over 200 times the speed of a current mid-range workstation, and is scalable to very large problems. The paper describes the network, how it is implemented and its performance.
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