Doctoral Dissertations
Date of Award
12-2022
Degree Type
Dissertation
Degree Name
Doctor of Philosophy
Major
Electrical Engineering
Major Professor
Garrett Rose
Committee Members
Nicole McFarlane, Andrew Sarles, Aziz Ahmedullah
Abstract
Alternative computing technologies are highly sought after due to limitations on transistor fabrication improvements. Fabricated memristive technology allows for a non-volatile analog memory for neuromorphic computing. In an integrated CMOS process, the synapse circuits designed for a spiking neuromorphic system can use memristors to regulate accumulation in the neuron circuits. Testing the fabricated memristive devices composed of hafnium oxide and developing a model to represent the key device characteristics lead to specific design choices in implementing the analog memory core of the synapse circuit. The circuits I designed for neuromorphic computing in this process take advantage of the unique capabilities of the memristive device to store a programmable analog memory reliably and efficiently. I designed the peripheral circuitry required including the circuits for programming the memristor and for online learning capabilities.
Recommended Citation
Weiss, Ryan, "Hardware for Memristive Neuromorphic Systems with Reliable Programming and Online Learning. " PhD diss., University of Tennessee, 2022.
https://trace.tennessee.edu/utk_graddiss/7703