C
Catherine D. Schuman
Researcher at Oak Ridge National Laboratory
Publications - 132
Citations - 2723
Catherine D. Schuman is an academic researcher from Oak Ridge National Laboratory. The author has contributed to research in topics: Neuromorphic engineering & Artificial neural network. The author has an hindex of 20, co-authored 112 publications receiving 1791 citations. Previous affiliations of Catherine D. Schuman include University of Tennessee.
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A Survey of Neuromorphic Computing and Neural Networks in Hardware.
Catherine D. Schuman,Thomas E. Potok,Robert M. Patton,J. Douglas Birdwell,Mark Edward Dean,Garrett S. Rose,James S. Plank +6 more
TL;DR: An exhaustive review of the research conducted in neuromorphic computing since the inception of the term is provided to motivate further work by illuminating gaps in the field where new research is needed.
Proceedings Article
A performance evaluation and examination of open-source erasure coding libraries for storage
TL;DR: A head-to-head comparison of codes and implementations is performed, to discern whether theory matches practice, and to demonstrate how parameter selection, especially as it concerns memory, has a significant impact on a code's performance.
Journal ArticleDOI
Opportunities for neuromorphic computing algorithms and applications
Catherine D. Schuman,Shruti R. Kulkarni,Maryam Parsa,J. Parker Mitchell,Prasanna Date,Bill Kay +5 more
TL;DR: A review of recent results in neuromorphic computing algorithms and applications can be found in this article , where the authors highlight characteristics of neuromorphic Computing technologies that make them attractive for the future of computing and discuss opportunities for future development of algorithms and application on these systems.
Journal ArticleDOI
Memristive Ion Channel-Doped Biomembranes as Synaptic Mimics.
Joseph S. Najem,Joseph S. Najem,Graham Taylor,Ryan J. Weiss,Sakib Hasan,Garrett S. Rose,Catherine D. Schuman,Alex Belianinov,C. Patrick Collier,Stephen A. Sarles +9 more
TL;DR: It is demonstrated that an alamethicin-doped, synthetic biomembrane exhibits memristive behavior, emulates key synaptic functions including paired-pulse facilitation and depression, and enables learning and computing.
Proceedings ArticleDOI
An evolutionary optimization framework for neural networks and neuromorphic architectures
TL;DR: This work describes an EO training framework for a spiking neural network architecture and a neuromorphic architecture, and presents the results of this training framework on four classification data sets and compares those results to other neural network and neuromorphic implementations.