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Hardware requirements for neural network pattern classifiers: a case study and implementation
January/February 1992 (vol. 12 no. 1)
pp. 32,33,34,35,36,37,38,39,40
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.<>
Index Terms:
neural nets,computerised pattern recognition,handwritten character recognition,neural network,pattern classifiers,special-purpose chip,data path,convolutional architectures,pattern classification networks,development system,rapid prototyping,Neural network hardware,Neural networks,Computer networks,Computer architecture,Pattern classification,Neurofeedback,Network topology,Prototypes,Performance analysis,System performance
Citation:
"Hardware requirements for neural network pattern classifiers: a case study and implementation," IEEE Micro, vol. 12, no. 1, pp. 32,33,34,35,36,37,38,39,40, Jan.-Feb. 1992, doi:10.1109/40.124378
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