Name
Abstract | ||
|---|---|---|
Neuromorphic computing hardware has undergone a rapid development and progress in the past few years. One of the key components in neuromorphic computing systems is the neural encoder which transforms sensory information into spike trains. In this paper, both rate encoding and temporal encoding schemes are discussed. Two novel temporal encoding schemes, parallel and iteration, are presented. The p... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TMSCS.2016.2607164 | IEEE Transactions on Multi-Scale Computing Systems |
Keywords | DocType | Volume |
Encoding,Neurons,Biomembranes,Neuromorphics,Semiconductor device modeling,Mathematical model,CMOS technology,Iterative methods | Journal | 2 |
Issue | ISSN | Citations |
4 | 2332-7766 | 1 |
PageRank | References | Authors |
0.35 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chenyuan Zhao | 1 | 27 | 4.57 |
| Bryant T. Wysocki | 2 | 65 | 6.76 |
| Clare D. Thiem | 3 | 1 | 0.35 |
| Nathan R. McDonald | 4 | 87 | 7.03 |
| Jialing Li | 5 | 1 | 0.35 |
| Lingjia Liu | 6 | 799 | 92.58 |
| Yang Yi | 7 | 159 | 26.70 |