DocumentCode :
821912
Title :
Hardware requirements for neural network pattern classifiers: a case study and implementation
Author :
Boser, Bernhard E. ; Sackinger, Eduard ; Bromley, Jane ; LeCun, Yann ; Jackel, Lawrence D.
Volume :
12
Issue :
1
fYear :
1992
Firstpage :
32
Lastpage :
40
Abstract :
A special-purpose chip, optimized for computational needs of neural networks and performing over 2000 multiplications and additions simultaneously, is described. Its data path is particularly suitable for the convolutional architectures typical in pattern classification networks but can also be configured for fully connected or feedback topologies. A development system permits rapid prototyping of new applications and analysis of the impact of the specialized hardware on system performance. The power and flexibility of the processor are demonstrated with a neural network for handwritten character recognition containing over 133000 connections.<>
Keywords :
computerised pattern recognition; neural nets; convolutional architectures; data path; development system; handwritten character recognition; neural network; pattern classification networks; pattern classifiers; rapid prototyping; special-purpose chip; Computer architecture; Computer networks; Network topology; Neural network hardware; Neural networks; Neurofeedback; Pattern classification; Performance analysis; Prototypes; System performance;
fLanguage :
English
Journal_Title :
Micro, IEEE
Publisher :
ieee
ISSN :
0272-1732
Type :
jour
DOI :
10.1109/40.124378
Filename :
124378
Link To Document :
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