DocumentCode :
675321
Title :
Cellular neural network computational scheme for efficient implementation of the FDTD method
Author :
Mayor, J. ; Tobon, Luis ; Nagy, Zsolt ; Tamura, Eugenio
Author_Institution :
Dept. de Ing. Electron. y Cienc. de la Comput., Pontificia Univ. Javeriana, Cali, Colombia
fYear :
2013
fDate :
7-13 July 2013
Firstpage :
79
Lastpage :
79
Abstract :
´Summaro form only given. A Cellular Neural Network (CNN) computational scheme is a processor array structure that emulates the most valuable parallelizing capabilities of the Artificial Neural Network (ANN) (L. Chua, L. Yang, Circuits and Systems, IEEE Tran, 1988). Each cell or processor inside the array has a specific processing capabilities depending on the mapped numerical application over it. This scheme has been proved in different applications that assure a PDE regular mesh mapping (A. Kiss, Z. Nagy, Journal of Circuit Theory and App, 2008).
Keywords :
cellular neural nets; finite difference time-domain analysis; microprocessor chips; ANN; CNN computational scheme; FDTD method; artificial neural network; cellular neural network computational scheme; parallelizing capabilities; Arrays; Cellular neural networks; Computers; Educational institutions; Finite difference methods; Geometry; Time-domain analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radio Science Meeting (Joint with AP-S Symposium), 2013 USNC-URSI
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
978-1-4799-1128-8
Type :
conf
DOI :
10.1109/USNC-URSI.2013.6715385
Filename :
6715385
Link To Document :
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