@inproceedings{d05ac24117f24961a25ab531e76e8ba8,
title = "A Spike-based Cellular-Neural Network Architecture for Spatiotemporal filtering",
abstract = "The foundation and architecture for a spike-based, neuromorphic cellular neural network is presented. Spike information from an event-based, dynamic vision sensor is processed asynchronously by the architecture in parallel. An array of N2 processing elements (PEs) with eight neighbor clique is the primitive unit of the processor. Spatiotemporal filtering of spike data is accomplised via mixed-signed, embedded morphological processing using a simplicial piecewise linear approximation. Preliminary simulation and modeling on data acquired from event-based sensors show a clear pathway towards the realization of the architecture in hardware.",
keywords = "Semiconductor device modeling, Computer architecture, Retina, Silicon, Data models, Spatiotemporal phenomena, Timing",
author = "Sengupta, {Jonah P.} and Martin Villemur and Andreou, {Andreas G.}",
note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; 2021 55th Annual Conference on Information Sciences and Systems (CISS) ; Conference date: 24-03-2021 Through 26-03-2021",
year = "2021",
month = mar,
day = "26",
doi = "10.1109/CISS50987.2021.9400308",
language = "English",
isbn = "9781665412681",
series = "2021 55th Annual Conference on Information Sciences and Systems, CISS 2021",
publisher = "IEEE Computer Society",
pages = "1--6",
booktitle = "2021 55th Annual Conference on Information Sciences and Systems, CISS 2021",
address = "United States",
}