Hardware requirements for neural network pattern classifiers: a case study and implementation

Boser, Bernhard E.; Sackinger, Eduard; Bromley, Jane; leCun, Yann and Jackel, Lawrence D. (1992). Hardware requirements for neural network pattern classifiers: a case study and implementation. IEEE Micro, 12(1) pp. 32–40.

DOI: https://doi.org/10.1109/40.124378

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.

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About

• Item ORO ID
• 35663
• Item Type
• Journal Item
• ISSN
• 0272-1732
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 1992 IEEE
• Depositing User
• Jane M. Bromley