Ryan Weiss, Gangotree Chakma and Garrett Rose

August, 2017

60th IEEE International Midwest Symposium on Circuits and Systems

http://www.mwscas2017.org

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Abstract

In this paper we present circuit techniques to optimize analog neurons specifically for operation in memristive neuromorphic systems. Since the peripheral circuits and control signals of the system are digital in nature, we take a mixed-signal circuit design approach to leverage analog computation in multiplying and accumulating digital input spikes and generate binary spikes as outputs to be consistent with surrounding synchronous digital logic circuits. A novel approach for synchronization is leveraged based on domino logic. The principal advantage of utilizing analog neurons within an overall digital system design is to ensure efficiency in size and power consumption. Energy per spike was determined to be 20 fJ, based on Cadence Spectre simulations of the proposed domino-based neural circuit.

Citation Information

Text

author     R. Weiss and G. Chakma and G. S. Rose
title      A Synchronized Axon Hillock Neuron for Memristive Neuromorphic Systems 
booktitle  60th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)
address    Boston, MA
month      August
year       2017
where      http://www.mwscas2017.org

Bibtex

@INPROCEEDINGS{wcr:17:asa,
    author = "R. Weiss and G. Chakma and G. S. Rose",
    title = "A Synchronized Axon Hillock Neuron for Memristive Neuromorphic Systems ",
    booktitle = "60th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)",
    address = "Boston, MA",
    month = "August",
    year = "2017",
    where = "http://www.mwscas2017.org"
}