John F. Pitrelli, Michael P. Perrone
ICDAR 2003
In this paper we present a new version of the standard multilayer perceptron (MLP) algorithm for the state-of-the-art in neural network VLSI implementations: the Intel Ni1000. This new version of the MLP uses a fundamental property of high dimensional spaces which allows the l2-norm to be accurately approximated by the l1-norm. This approach enables the standard MLP to utilize the parallel architecture of the Ni1000 to achieve on the order of 40000, 256-dimensional classifications per second.
John F. Pitrelli, Michael P. Perrone
ICDAR 2003
John F. Pitrelli, Jayashree Subrahmonia, et al.
IJDAR
Krishna S. Nathan, Jayashree Subrahmonia, et al.
ICPR 1996
Michael P. Perrone, Gregory F. Russell, et al.
IBM Systems Journal