Unsupervised character recognition with a simplified FPGA neuromorphic system

Corey Lammie, Tara Hamilton, Mostafa Rahimi Azghadi

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

28 Citations (Scopus)

Abstract

![CDATA[Neuromorphic hardware platforms have demonstrated significant promise in cognitive tasks such as visual processing and classification. These platforms usually consist of several layers of spiking neurons for feature extraction and various learning mechanisms, which renders the associated networks power and hardware hungry. In this paper, we have implemented a simplified proof-of-concept Spiking Neural Network (SNN) on a Field Programmable Gate Array (FPGA) and trained it using Spike Timing Dependent Plasticity (STDP) to identify temporally encoded characters, in an unsupervised manner. The constructed one-layer network consists of excitatory synapses, which receive input characters in the form of Poissonian spike trains from the pre-synaptic side. From the post-synaptic side, the synapses are connected to output Izhikevich neurons. In addition, non-plastic inhibitory synapses between the output neurons are introduced to implement lateral inhibition and competitive learning. The implemented neural hardware demonstrates a powerful and fast learning scheme, which brings about a significant unsupervised classification accuracy of 94 %. In addition, since the proposed network receives the characters in the form of spike trains, it is amenable to being interfaced to neuromorphic event-driven sensors such as silicon retina, making the proposed platform useful for online unsupervised template matching applications.]]
Original languageEnglish
Title of host publication2018 IEEE International Symposium on Circuits and Systems (ISCAS): Proceedings, 27-30 May 2018, Florence, Italy
PublisherIEEE
Number of pages5
ISBN (Print)9781538648810
DOIs
Publication statusPublished - 2018
EventIEEE International Symposium on Circuits and Systems -
Duration: 27 May 2018 → …

Publication series

Name
ISSN (Print)2379-447X

Conference

ConferenceIEEE International Symposium on Circuits and Systems
Period27/05/18 → …

Keywords

  • field programmable gate arrays
  • neural networks (computer science)
  • neuromorphics
  • optical character recognition

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