DocumentCode
1838016
Title
CNN using memristors for neighborhood connections
Author
Lehtonen, E. ; Laiho, M.
Author_Institution
Dept. of Inf. Technol., Univ. of Turku, Turku, Finland
fYear
2010
fDate
3-5 Feb. 2010
Firstpage
1
Lastpage
4
Abstract
In this paper we consider using memristors to implement the neighborhood connections of a CNN. First the benefits and drawbacks of using memristors as programmable CNN weights are described. Then, an existing memristor model is improved to allow full-scale simulation of the design. The new model is implemented in the SPICE simulation environment and is not restricted to CNN applications. Then, the CNN cell design is presented and simulations describing memristor programming are performed.
Keywords
cellular neural nets; logic design; memristors; CNN cell design; CNN neighborhood connections; SPICE simulation environment; cellular neural networks; memristor programming; programmable CNN weights; Analog memory; Cellular networks; Cellular neural networks; Circuits; Information technology; Memristors; Neural networks; SPICE; Virtual manufacturing; Voltage; CNN cell; Cellular nonlinear neural networks; Memristor; Model;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Nanoscale Networks and Their Applications (CNNA), 2010 12th International Workshop on
Conference_Location
Berkeley, CA
Print_ISBN
978-1-4244-6679-5
Type
conf
DOI
10.1109/CNNA.2010.5430304
Filename
5430304
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