Name
Title | ||
|---|---|---|
A Hardware-Efficient Calibrator for SAR-Pipelined ADCs with a Layer-based Sharing Neural Network |
Abstract | ||
|---|---|---|
Although the calibrator based on neural networks performs well in nonlinearity calibration for SAR-Pipelined ADC, it suffers from considerable hardware complexity. This paper proposes a network structure called layer-based neural network (LSNN) to optimize this calibrator. Compared with the traditional structures, LSNN has the following advantages. First, it optimizes storage and logic simultaneou... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MWSCAS47672.2021.9531920 | 2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS) |
Keywords | DocType | ISSN |
Backpropagation,Circuits and systems,Neural networks,Area measurement,Bandwidth,Loss measurement,Hardware | Conference | 1548-3746 |
ISBN | Citations | PageRank |
978-1-6654-2461-5 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min Chen | 1 | 0 | 1.01 |
| Nuo Xu | 2 | 14 | 7.66 |
| Yutong Zhao | 3 | 1 | 2.05 |
| Fan Ye | 4 | 34 | 21.14 |
| Junyan Ren | 5 | 154 | 41.40 |