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)
- 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.