Neuromorphic Computing at Tennessee
We are a group of faculty, post-docs, graduate students and undergraduates researching a new paradigm of computing, inspired by the human brain. Our research encompasses nearly every facet of the area, including current and emergent hardware implementations, theoretical models, programming techniques and applications. (Read More)
Publications
Recent Publications
- A Practical Hafnium-Oxide Memristor Model Suitable for Circuit Design and Simulation: ISCAS: International Symposium on Circuits and Systems May, 2017.
- A Survey of Neuromorphic Computing and Neural Networks in Hardware: Published on Arxiv. May, 2017.
- Structure-based Fitness Prediction for the Variable-structure DANNA Neuromorphic Architecture: IJCNN: The International Joint Conference on Neural Networks May, 2017.
- The Effect of Biologically-Inspired Mechanisms in Spiking Neural Networks for Neuromorphic Implementation: IJCNN: The International Joint Conference on Neural Networks May, 2017.
- Circuit Techniques for Online Learning of Memristive Synapses in CMOS-Memristor Neuromorphic Systems: 27th ACM Great Lakes Symposium on VLSI May, 2017.
All Publications
Team
Dr. Roger Horn
Musabbir Adnan
Sherif Amer
Ksenia Burova
Gangotree Chakma
Adam Disney
Patricia Eckhart
Parker Mitchell
John Murray
Michael Peek
John Reynolds
Sagarvarma Sayyaparaju
Ryan Weiss
Clarence Wong
Austin Wyer
Aaron Young
Sam Brown
Grant Bruer
MaryBeth Burst
Trevor Dixon
Michael Goin
Philip McKnight
Nick Skuda
Grace Zhao