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Poster: Dynamic Adaptive Neural Network Arrays -- A Neuromorphic Platform

Adam Disney

September, 2016

SMC16: Smoky Mountain Computational Sciences and Engineering Conference

http://computing.ornl.gov/workshops/SMC16

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Abstract

Conventional microprocessor speed has plateaued, and thus researchers are looking for alternative computing technologies. At the University of Tennessee, we are looking to the human brain for inspiration. We have developed a Neuromorphic computing model, called Dynamic Adaptive Neural Network Arrays (DANNA), that computes with neurons and synapses in a real time manner known as a spiking neural network. This system has been implemented in software and on FPGAs. Using these implementations, we have developed two control applications: pole balancing and a one-dimensional navigation engine.

Citation Information

Text


author        A. Disney
title         Dynamic Adaptive Neural Network Arrays -- A Neuromorphic Platform
howpublished  Poster presented at SMC16: Smoky Mountain Computational Sciences and Engineering Conference
year          2016
publisher     Oak Ridge National Laboratory
address       Gatlinburg, TN
url           http://computing.ornl.gov/workshops/SMC16
where         http://neuromorphic.eecs.utk.edu/publications/2016-09-02-dynamic-adaptive-neural-network-arrays-a-neuromorphic-platform/

Bibtex


@MISC{d:16:dan,
    author = "A. Disney",
    title = "Dynamic Adaptive Neural Network Arrays -- A Neuromorphic Platform",
    howpublished = "Poster presented at SMC16: Smoky Mountain 
            Computational Sciences and Engineering Conference",
    year = "2016",
    publisher = "Oak Ridge National Laboratory",
    address = "Gatlinburg, TN",
    url = "http://computing.ornl.gov/workshops/SMC16",
    where = "http://neuromorphic.eecs.utk.edu/publications/2016-09-02-dynamic-adaptive-neural-network-arrays-a-neuromorphic-platform/"
}