Name
Abstract | ||
|---|---|---|
A compact low-power CMOS analog circuit implementation of a Cellular Neural Network which uses continuously programmable weight values has been presented recently. Now the operation of this full signal range CNN in image filtering is verified through simulation. A learning tool comprising a friendly graphical interface and the center of mass learning algorithm has been developed, which made it possible to determine optimal coefficients for CNN application in image filtering. Circuit simulations of low-pass and high-pass filters have been accomplished with satisfactory results. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/LASCAS.2015.7250426 | 2015 IEEE 6th Latin American Symposium on Circuits & Systems (LASCAS) |
Keywords | Field | DocType |
CMOS analog CNN,frequency-domain image filtering,CNN learning algorithm | Computer science,Filter (signal processing),CMOS,Electronic engineering,Graphical user interface,Cellular neural network | Conference |
ISSN | Citations | PageRank |
2330-9954 | 1 | 0.41 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| fabian souza de andrade | 1 | 2 | 2.85 |
| ygor oliveira da guarda souza | 2 | 1 | 0.41 |
| edson pinto santana | 3 | 4 | 4.10 |
| A. I. A. Cunha | 4 | 5 | 2.48 |