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Nanostructure array of coupled RTDs as cellular neural networks
Author(s) -
Karahaliloglu Koray,
Balkir Sina
Publication year - 2003
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.251
Subject(s) - nanodevice , cellular neural network , artificial neural network , computer science , reaction–diffusion system , smoothing , enhanced data rates for gsm evolution , memristor , image processing , electronic engineering , biological system , topology (electrical circuits) , artificial intelligence , nanotechnology , image (mathematics) , engineering , materials science , electrical engineering , physics , biology , computer vision , thermodynamics
The processing capabilities of a proposed nanoelectronic device are investigated. The device is considered as a global dynamical system with local circuit model components. The system equations and the corresponding network model are presented. The characteristics of this network model are compared with the cellular neural networks. Certain characteristics of the network are analysed theoretically and demonstrated with circuit‐system level simulations. As a novel property, it is shown that the single layer nanodevice network structure is a basic reaction–diffusion system and it is capable of autowave propagation. Furthermore, the same network structure exhibits several image processing capabilities like image smoothing, edge enhancement, and horizontal or vertical line detection using simple arrangements of the device parameters. Copyright ©2003 John Wiley & Sons, Ltd.