A compact multi-chip-module implementation of a multi-precision neural network classifier
Amine Bermak, Dominique Martinez · 2002
This paper describes a novel MCM digital implementation of a reconfigurable multi-precision neural network classifier. The design is based on a scalable systolic architecture with a user defined topology and arithmetic precision of the neural network. Indeed, the MCM integrates 64/32/16 neurons with a corresponding accuracy of 4/8/16-bits. A prototype has been designed and successfully tested in CMOS 0.7 /spl mu/m technology.