A 3.2-GHz 1.3-mW ILO phase rotator for burst-mode mobile memory I/O in 28-nm low-leakage CMOS
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: 2014DOI: 10.1109/ICPHM.2014.7036390
Keyword(s): Artificial neural networks,Batteries,Battery charge measurement,Estimation,Kalman filters,Mathematical model,System-on-chip,DEKF,Li-ion battery,battery management system,neural networks,state-of-health,state-ofcharge
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A 3.2-GHz 1.3-mW ILO phase rotator for burst-mode mobile memory I/O in 28-nm low-leakage CMOS
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| contributor author | Aleksic, M. | |
| date accessioned | 2020-03-12T21:25:14Z | |
| date available | 2020-03-12T21:25:14Z | |
| date issued | 2014 | |
| identifier other | 6942119.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1048534?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | A 3.2-GHz 1.3-mW ILO phase rotator for burst-mode mobile memory I/O in 28-nm low-leakage CMOS | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8177969 | |
| subject keywords | Artificial neural networks | |
| subject keywords | Batteries | |
| subject keywords | Battery charge measurement | |
| subject keywords | Estimation | |
| subject keywords | Kalman filters | |
| subject keywords | Mathematical model | |
| subject keywords | System-on-chip | |
| subject keywords | DEKF | |
| subject keywords | Li-ion battery | |
| subject keywords | battery management system | |
| subject keywords | neural networks | |
| subject keywords | state-of-health | |
| subject keywords | state-ofcharge | |
| identifier doi | 10.1109/ICPHM.2014.7036390 | |
| journal title | uropean Solid State Circuits Conference (ESSCIRC), ESSCIRC 2014 - 40th | |
| filesize | 3055669 | |
| citations | 0 |