Integrated Models and Their Usage in Predicting the Signal Strength
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: 2014DOI: 10.1109/HPCSim.2014.6903727
Keyword(s): neural nets,n reconfigurable architectures,n DRRA cell,n NeuroCGRA,n audio acquisition,n audio recognition,n coarse grained reconfigurable architectures,n dynamically reconfigurable resource array,n image recognition,n neural networks,n video acquisition,n video recognition,n Biological neural networks,n Computer architecture,n Field programmable gate arrays,n Image edge detection,n Neurons,n Registers
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Integrated Models and Their Usage in Predicting the Signal Strength
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| contributor author | Lee, David J.Y. | |
| contributor author | Lee, William C.Y. | |
| date accessioned | 2020-03-12T22:46:05Z | |
| date available | 2020-03-12T22:46:05Z | |
| date issued | 2014 | |
| identifier other | 7022949.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1093876?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Integrated Models and Their Usage in Predicting the Signal Strength | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8233442 | |
| subject keywords | neural nets | |
| subject keywords | n reconfigurable architectures | |
| subject keywords | n DRRA cell | |
| subject keywords | n NeuroCGRA | |
| subject keywords | n audio acquisition | |
| subject keywords | n audio recognition | |
| subject keywords | n coarse grained reconfigurable architectures | |
| subject keywords | n dynamically reconfigurable resource array | |
| subject keywords | n image recognition | |
| subject keywords | n neural networks | |
| subject keywords | n video acquisition | |
| subject keywords | n video recognition | |
| subject keywords | n Biological neural networks | |
| subject keywords | n Computer architecture | |
| subject keywords | n Field programmable gate arrays | |
| subject keywords | n Image edge detection | |
| subject keywords | n Neurons | |
| subject keywords | n Registers | |
| identifier doi | 10.1109/HPCSim.2014.6903727 | |
| journal title | ehicular Technology Conference (VTC Spring), 2014 IEEE 79th | |
| filesize | 4070687 | |
| citations | 0 |