Name
Title | ||
|---|---|---|
Session 13 overview: Machine learning and signal processing: Digital architectures and systems subcommittee. |
Abstract | ||
|---|---|---|
Architectures supporting machine learning for embedded perception and cognition are continuing their rapid evolution, inspired by modern data analytics and enabled by the low energy cost of CMOS processing. This makes it feasible to migrate data analytics toward edge and wearable devices. To further support increased requirements for multiuser connectivity and sparse data, multiuser MIMO and compressive reconstruction are also required. |
Year | Venue | Field |
|---|---|---|
2018 | ISSCC | Signal processing,Low energy,Data analysis,Computer science,MIMO,Cmos process,Artificial intelligence,Wearable technology,Perception,Machine learning,Sparse matrix |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dejan Markovic | 1 | 811 | 115.54 |
| Masato Motomura | 2 | 8 | 3.65 |
| Byeong-Gyu Nam | 3 | 118 | 12.83 |