Stochastic computing & stochastic resonance in digital & analog neuromorphic systems.
| dc.contributor.advisor | Koziol, Scott M. | |
| dc.creator | Boline, Jacob, 1992- | |
| dc.date.accessioned | 2021-01-28T15:38:24Z | |
| dc.date.available | 2021-01-28T15:38:24Z | |
| dc.date.created | 2020-12 | |
| dc.date.issued | 2020-11-17 | |
| dc.date.submitted | December 2020 | |
| dc.date.updated | 2021-01-28T15:38:24Z | |
| dc.description.abstract | Stochastic computing is an alternative method to standard deterministic methods. This thesis explores stochastic resonance in a spiking neuron, and leverages the effects it has to implement stochastic computing in an analog spiking neuron, and simple neuron network. In addition, a method for interfacing a Stochastic Artificial Neural Network implemented on a Field Programmable Gate Array with a computer running MATLAB is presented. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/2104/11209 | |
| dc.language.iso | en | |
| dc.rights.accessrights | No access – contact librarywebmaster@baylor.edu | |
| dc.subject | Stochastic computing. Stochastic resonance. Artificial neural network. | |
| dc.title | Stochastic computing & stochastic resonance in digital & analog neuromorphic systems. | |
| dc.type | Thesis | |
| dc.type.material | text | |
| local.embargo.lift | 2025-12-01 | |
| local.embargo.terms | 2025-12-01 | |
| thesis.degree.department | Baylor University. Dept. of Electrical & Computer Engineering. | |
| thesis.degree.grantor | Baylor University | |
| thesis.degree.level | Masters | |
| thesis.degree.name | M.S.E.C.E. |
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