Title:
Can my chip behave like my brain?
Can my chip behave like my brain?
| dc.contributor.advisor | Hasler, Jennifer | |
| dc.contributor.author | George, Suma | |
| dc.contributor.committeeMember | Anderson, David | |
| dc.contributor.committeeMember | Inan, Omer | |
| dc.contributor.committeeMember | Wang, Hua | |
| dc.contributor.committeeMember | Pfeiffer, Michael | |
| dc.contributor.department | Electrical and Computer Engineering | |
| dc.date.accessioned | 2016-05-27T13:11:04Z | |
| dc.date.available | 2016-05-27T13:11:04Z | |
| dc.date.created | 2015-05 | |
| dc.date.issued | 2015-04-07 | |
| dc.date.submitted | May 2015 | |
| dc.date.updated | 2016-05-27T13:11:04Z | |
| dc.description.abstract | Many decades ago, Carver Mead established the foundations of neuromorphic systems. Neuromorphic systems are analog circuits that emulate biology. These circuits utilize subthreshold dynamics of CMOS transistors to mimic the behavior of neurons. The objective is to not only simulate the human brain, but also to build useful applications using these bio-inspired circuits for ultra low power speech processing, image processing, and robotics. This can be achieved using reconfigurable hardware, like field programmable analog arrays (FPAAs), which enable configuring different applications on a cross platform system. As digital systems saturate in terms of power efficiency, this alternate approach has the potential to improve computational efficiency by approximately eight orders of magnitude. These systems, which include analog, digital, and neuromorphic elements combine to result in a very powerful reconfigurable processing machine. | |
| dc.description.degree | Ph.D. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/54905 | |
| dc.publisher | Georgia Institute of Technology | |
| dc.subject | Neuromorphic | |
| dc.subject | Reconfigurable | |
| dc.subject | Mixed signal | |
| dc.subject | FPAA | |
| dc.subject | Dendrites | |
| dc.subject | RASP | |
| dc.subject | CAD tools | |
| dc.subject | Heterogeneous architectures | |
| dc.title | Can my chip behave like my brain? | |
| dc.type | Text | |
| dc.type.genre | Dissertation | |
| dspace.entity.type | Publication | |
| local.contributor.advisor | Hasler, Jennifer | |
| local.contributor.corporatename | School of Electrical and Computer Engineering | |
| local.contributor.corporatename | College of Engineering | |
| relation.isAdvisorOfPublication | da2ccc86-1c57-49e7-b766-ceb2f9a4eac5 | |
| relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
| relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 | |
| thesis.degree.level | Doctoral |