Name
Title | ||
|---|---|---|
Analog Learning Neural Network using Two-Stage Mode by Multiple and Sample Hold Circuits |
Abstract | ||
|---|---|---|
In the neural network field, many application models have been proposed. A neuro chip and an artificial retina chip are developed to comprise the neural network model and simulate the biomedical vision system. Previous analog neural network models were composed of the operational amplifier and fixed resistance. It is difficult to change the connection coefficient. In this study, we used analog electronic multiple and sample hold circuits. The connecting weights describe the input voltage. It is easy to change the connection coefficient. This model works only on analog electronic circuits. It can finish the learning process in a very short time and this model will enable more flexible learning. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.4018/ijsi.2014010105 | International Journal of Software Innovation |
Keywords | Field | DocType |
Biomedical Vision System, Electronic Circuit, Flexible Learning, Multiple Circuit, Neural Network | Physical neural network,Machine vision,Computer science,Voltage,Electronic engineering,Chip,Time delay neural network,Electronic circuit,Artificial neural network,Operational amplifier | Journal |
Volume | Issue | ISSN |
2 | 1 | 2166-7160 |
Citations | PageRank | References |
1 | 0.41 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Masashi Kawaguchi | 1 | 24 | 14.93 |
| Naohiro Ishii | 2 | 461 | 128.62 |
| Takashi Jimbo | 3 | 15 | 7.35 |