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