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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Modeling and Experimental Demonstration of a Hopfield Network Analog-to-Digital Converter with Hybrid CMOS/Memristor Circuits
|
|---|---|
| Published in |
Frontiers in Neuroscience, December 2015
|
| DOI | 10.3389/fnins.2015.00488 |
| Pubmed ID | |
| Authors |
Xinjie Guo, Farnood Merrikh-Bayat, Ligang Gao, Brian D. Hoskins, Fabien Alibart, Bernabe Linares-Barranco, Luke Theogarajan, Christof Teuscher, Dmitri B. Strukov |
| Abstract |
The purpose of this work was to demonstrate the feasibility of building recurrent artificial neural networks with hybrid complementary metal oxide semiconductor (CMOS)/memristor circuits. To do so, we modeled a Hopfield network implementing an analog-to-digital converter (ADC) with up to 8 bits of precision. Major shortcomings affecting the ADC's precision, such as the non-ideal behavior of CMOS circuitry and the specific limitations of memristors, were investigated and an effective solution was proposed, capitalizing on the in-field programmability of memristors. The theoretical work was validated experimentally by demonstrating the successful operation of a 4-bit ADC circuit implemented with discrete Pt/TiO2- x /Pt memristors and CMOS integrated circuit components. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 78 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 23% |
| Researcher | 14 | 18% |
| Student > Master | 8 | 10% |
| Other | 5 | 6% |
| Student > Doctoral Student | 5 | 6% |
| Other | 8 | 10% |
| Unknown | 20 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 35 | 45% |
| Computer Science | 6 | 8% |
| Physics and Astronomy | 5 | 6% |
| Materials Science | 5 | 6% |
| Economics, Econometrics and Finance | 1 | 1% |
| Other | 5 | 6% |
| Unknown | 21 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 30 August 2022.
All research outputs
#7,779,140
of 25,374,917 outputs
Outputs from Frontiers in Neuroscience
#4,921
of 11,541 outputs
Outputs of similar age
#112,002
of 396,487 outputs
Outputs of similar age from Frontiers in Neuroscience
#54
of 120 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 11,541 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 56% 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 396,487 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.