| Title |
Adaptive learning rule for hardware-based deep neural networks using electronic synapse devices
|
|---|---|
| Published in |
Neural Computing and Applications, July 2018
|
| DOI | 10.1007/s00521-018-3659-y |
| Authors |
Suhwan Lim, Jong-Ho Bae, Jai-Ho Eum, Sungtae Lee, Chul-Heung Kim, Dongseok Kwon, Byung-Gook Park, Jong-Ho Lee |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 52 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 21% |
| Student > Master | 11 | 21% |
| Researcher | 3 | 6% |
| Other | 2 | 4% |
| Lecturer | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 19 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 21 | 40% |
| Computer Science | 5 | 10% |
| Neuroscience | 3 | 6% |
| Materials Science | 2 | 4% |
| Physics and Astronomy | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 19 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 August 2017.
All research outputs
#14,608,511
of 23,839,820 outputs
Outputs from Neural Computing and Applications
#367
of 2,407 outputs
Outputs of similar age
#181,386
of 331,379 outputs
Outputs of similar age from Neural Computing and Applications
#2
of 8 outputs
Altmetric has tracked 23,839,820 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,407 research outputs from this source. They receive a mean Attention Score of 1.3. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,379 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.