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
Link To Document :
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