Name
Abstract | ||
|---|---|---|
Cellular Neural Networks(CNN) is a neural network model linked to only neighborhoods. CNN is suited for image processing such as noise reduction and edge detection. Small World Cellular Neural Networks(SWCNN) is a CNN extended by adding a small world link, which is global short-cut. SWCNN has better performance than CNN. One of weak points of SWCNN is fault tolerance. We proposed multiple SWCNN layers in order to improve fault tolerance of SWCNN. However it is not suf cient because only stop failure is considered. In this paper we propose Stateful Reliability Counter for Triple Modular Redundancy(Stateful RC-TMR) method in order to improve tolerance. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CISIS.2009.112 | CISIS: 2009 INTERNATIONAL CONFERENCE ON COMPLEX, INTELLIGENT AND SOFTWARE INTENSIVE SYSTEMS, VOLS 1 AND 2 |
Keywords | Field | DocType |
fault tolerance,pattern recognition,edge detection,noise,image processing,maintenance engineering,radiation detectors,cellular neural networks,neural networks,noise reduction,cellular networks,neural network model,fault tolerant,triple modular redundancy,cellular neural network | Computer science,Edge detection,Computer network,Triple modular redundancy,Image processing,Fault tolerance,Stateful firewall,Artificial neural network,Cellular neural network,Maintenance engineering,Distributed computing | Conference |
Citations | PageRank | References |
2 | 0.59 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Katsuyoshi Matsumoto | 1 | 46 | 8.45 |
| Minoru Uehara | 2 | 525 | 96.87 |
| Motoi Yamagiwa | 3 | 80 | 15.51 |
| Makoto Murakami | 4 | 33 | 6.01 |
| Hideki Mori | 5 | 99 | 18.12 |