An analog neural network processor and its application to high-speed character recognition

Boser, Bernhard E.; Säckinger, Eduard; Bromley, Jane; LeCun, Yann; Howard, Richard E. and Jackel, Lawrence D. (1991). An analog neural network processor and its application to high-speed character recognition. In: IJCNN-91- International Joint Conference on Neural Networks, 8-14 Jul 1991, Seattle, WA, USA, pp. 415–420.

DOI: https://doi.org/10.1109/IJCNN.1991.155214

Abstract

A high-speed programmable neural network chip and its application to character recognition are described. A network with over 130,000 connections has been implemented on a single chip and operates at a rate of over 1000 classifications per second. The chip performs up to 2000 multiplications and additions simultaneously. Its datapath is suitable particularly for the convolutional architectures that are typical in pattern classification networks, but can also be configured for fully connected or feedback topologies. Computations were performed with 6 bits accuracy for the weights and 3 bits for the states. The chip uses analog processing internally for higher density and reduced power dissipation, but all input/output is digital to simplify system integration

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